Explore 8 quantitative developer jobs from 3 hiring companies in Commerce, TX, US. Filter by remote, salary, experience, and company, then open any listing to apply.

quantitative-developer

Quantitative Developer

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Quantitative Developer Jobs

Goldman Sachs

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Asset &amp; Wealth Management –Analyst Quantitative Strategist in PWM Portfolio Analytics:
Our quantitative strategists are at the cutting edge of our business and solve real-world problems through a variety of analytical methods. As a member of our team, you will use your training in mathematics, programming, and logical thinking to construct quantitative models that drive our success in global financial markets. Your problem-solving talents and aptitude for innovation will help define your contributions and enable you to find solutions to a broad range of problems, in a dynamic, fast-paced environment.
As a strategist on our portfolio analytics team within our premier Goldman Sachs Private Wealth Management business, you will collaborate closely with financial professionals in the PWM business to combine quantitative techniques and industry knowledge to help design and refine investment strategies tailored for our PWM clients. You will be expected to develop a deep understanding of a wide range of financial products.
Responsibilities include:
<ul>
 <li>Working closely with wealth management professionals to design and create client reporting tools</li>
 <li>Working with senior leadership on business analytics and marketing efforts</li>
 <li>Providing backtests, risk analytics, and other analyses of PWM’s investment strategies</li>
 <li>Developing simulations to quantify benefits of PWM strategies and help drive client engagement</li>
 <li>Developing standardized &amp; scalable client reporting for an extensive client base, along with customized and bespoke analytics for the division’s largest and most sophisticated clients</li>
 <li>Building and maintaining infrastructure of Strategists’ analytical systems in a resource efficient manner</li>
</ul>
&nbsp;About Goldman Sachs PWM:
Goldman Sachs Private Wealth Management (PWM) is a world-class provider of wealth management solutions for high-net-worth individuals, their families, and foundations. Our PWM advisors help clients manage their financial wealth including providing access to innovative investment ideas and opportunities, developing customized investment strategies, and offering a full array of wealth management services.
&nbsp;Qualifications:
<ul>
 <li>Bachelor or Masters in a quantitative or engineering field, e.g. mathematics, physics, quantitative finance, computational finance, computer science, engineering</li>
 <li>Programming and mathematical skills are required</li>
 <li>Interest and knowledge of the financial markets. Keen to understand all facets of Private Wealth Management business.</li>
 <li>Intelligence, creativity, and problem-solving skills</li>
 <li>Great communication skills (written and verbal)</li>
 <li>A self-starter, should have ability to work independently as well as thrive in a team environment</li>
</ul>
ABOUT GOLDMAN SACHS
At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at&nbsp;<a href="http://gs.com/careers" target="_blank">GS.com/careers</a>.&nbsp;
We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more:&nbsp;<a href="https://www.goldmansachs.com/careers/footer/disability-statement.html%C2%A9" target="_blank">https://www.goldmansachs.com/careers/footer/disability-statement.html©</a>
The Goldman Sachs Group, Inc., 2023. All rights reserved.
Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.

Asset & Wealth Management - Quantitative Engineer - Analyst - Dallas

Quantitative Engineer

Bachelor’s or Master’s in a quantitative/engineering field; programming and math skills; interest in financial markets; strong problem-solving and communication skills; ability to work independently and in a team.

<div style="font-style:normal; font-weight:400">
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 Job Overview:&nbsp;
 The Quantitative Engineer will be responsible for the design, development, and implementation of quantitative models and algorithms for a financial services company. This individual will work closely with traders, portfolio managers, and other stakeholders to streamline reporting identify areas where quantitative analysis can provide insights and support decision-making.&nbsp;
 &nbsp;
 Key Responsibilities:
 <ul>
 <li>Coverage all aspects of private business, with focus on validation, streamlining and reporting for illiquid and semi-liquid funds</li>
 <li>Develop and implement quantitative models and algorithms to support trading and investment strategies</li>
 <li>Conduct statistical and mathematical analysis of financial data to identify patterns and trends</li>
 <li>Collaborate with traders, portfolio managers, and other stakeholders to identify areas where quantitative analysis can provide insights and support decision-making</li>
 <li>Communicate results and findings to stakeholders in a clear and concise manner</li>
 <li>Stay current with industry developments and new technologies</li>
 </ul>
 Qualifications:
 <ul>
 <li>Advanced degree in a related field such as Mathematics, Physics, Computer Science, Financial Engineering or a related field.</li>
 <li>Strong programming skills in at least one language such as Python, C++ or Java</li>
 <li>Strong understanding of mathematical and statistical concepts, especially in finance</li>
 <li>Strong problem-solving skills and the ability to think critically</li>
 <li>Excellent communication skills and the ability to work well in a team environment</li>
 <li>Experience and interest in financial markets, risk management and portfolio management</li>
 </ul>
 Experience:
 <ul>
 <li>Minimum of 2+ years of experience in a quantitative role in a financial services company</li>
 <li>Background in equity or credit preferred</li>
 <li>Full stack development or Secdb/Slang experience preferred</li>
 </ul>
 </div>
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<div style="font-style:normal; font-weight:400">
 ABOUT GOLDMAN SACHS
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<div style="font-style:normal; font-weight:400">
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</div>
<div style="font-style:normal; font-weight:400">
 At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.&nbsp; 
 
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</div>
<div style="font-style:normal; font-weight:400">
 We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers.&nbsp;
</div>
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<div style="font-style:normal; font-weight:400">
 We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html 
 
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<div style="font-style:normal; font-weight:400">
 © The Goldman Sachs Group, Inc., 2023. All rights reserved.
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<div style="font-style:normal; font-weight:400">
 Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity
</div>

Asset & Wealth Management - Quantitative Engineering - Associate - Dallas

Advanced degree in Mathematics, Physics, Computer Science, Financial Engineering, or related field; strong Python/C++/Java; finance math knowledge; 2+ years in a quantitative role; strong communication and teamwork.

Asset & Wealth Management

About Goldman Sachs Wealth Management
Across Wealth Management, Goldman Sachs helps empower clients and customers around the world to reach their financial goals. Our advisor-led wealth management businesses provide financial planning, investment management, banking, and comprehensive advice to a wide range of clients, including ultra-high net worth and high net worth individuals, as well as family offices, foundations and endowments, and corporations and their employees. Our consumer business provides digital solutions for customers to better spend, borrow, invest, and save. Across Wealth Management, our growth is driven by a relentless focus on our people, our clients and customers, and leading-edge technology, data, and design.Our quantitative strategists are at the cutting edge of our business and solve real-world problems through a variety of analytical methods. As a member of our team, you will utilize your training in mathematics, programming, and logical thinking to build quantitative models that drive success in our business. Your problem-solving talents and aptitude for innovation will help define your contributions and enable you to find solutions to a broad range of problems, in a dynamic, fast-paced environment.&nbsp;
Responsibilities
As a strategist on our PWM Risk Strats team, you will work&nbsp;closely with various teams including risk management and fraud strategy.&nbsp;You will combine quantitative techniques and industry knowledge to build best in class models and tools that streamline risk management, detect fraud at scale, enable optimized data-driven business decision making, and optimize profitability.
Responsibilities include:
<ul>
 <li>Developing and deploying ML models for fraud and anomaly detection as well as business workflows enhancement</li>
 <li>Delivering risk metrics and quantitative analytics for financial and non-financial risks across wealth management</li>
 <li>Develop AI-led solutions to improve efficiency and accuracy in risk management.</li>
 <li>Building and maintaining robust and systematic risk management tools and reporting</li>
 <li>Collaborating on the design of new and existing strategies to address clients’ investment goals.</li>
 <li>Developing and maintaining risk management and portfolio analysis tools across multiple asset classes for senior management and portfolio managers.</li>
 <li>Building and maintaining infrastructure of Strategists’ analytical systems.</li>
</ul>
Basic Qualifications
<ul>
 <li>Bachelor, Masters or Ph.D. in a quantitative or engineering field, e.g. mathematics, physics, quantitative finance, computational finance, computer science, engineering</li>
 <li>1-3 years of experience in the job offered or related quantitative financial modeling and software development positions</li>
 <li>Programming and mathematical skills are required</li>
 <li>Creativity, problem-solving skills, and ability to communicate complex ideas to a variety of audiences&nbsp;</li>
 <li>A self-starter, should have ability to work independently as well as thrive in a team environment</li>
 <li>Excellent understanding of machine learning techniques and algorithms, such as gradient boosting decision trees, random forests, etc., is a plus</li>
 <li>Experience with building models using common data science toolkits, i.e., Python (Pandas, NumPy, Scikit-learn) and Spark</li>
 <li>Experience with prompt engineering, working with LLM models, and MCP.</li>
 <li>Previous work experience in: Utilizing statistical methods, including time-series and regression analysis; programming in object-oriented languages for efficient model implementations; manipulating data sets using relational databases and SQL</li>
</ul>
Preferred Qualifications
<ul>
 <li>Excellent understanding of machine learning techniques and algorithms, such as gradient boosting decision trees, random forests, etc., is a plus</li>
 <li>Experience with building models using common data science toolkits, i.e., Python (Pandas, NumPy, Scikit-learn) and Spark</li>
 <li>Experience with prompt engineering, working with LLM models, and MCP.</li>
 <li>Previous work experience in: Utilizing statistical methods, including time-series and regression analysis; programming in object-oriented languages for efficient model implementations; manipulating data sets using relational databases and SQL</li>
</ul>
ABOUT GOLDMAN SACHS
At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.&nbsp;
We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers.&nbsp;
We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html
© The Goldman Sachs Group, Inc., 2021. All rights reserved.
Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity

Asset & Wealth Management - Quantitative Strategist - Associate - Dallas

Quantitative Strategist

Bachelor to PhD in quantitative/engineering field; 1-3 years in quantitative modeling or software development; strong programming and ML knowledge.

Our quantitative strategists are at the cutting edge of our business and solve real-world problems through a variety of analytical methods. As a member of our team, you will utilize your training in mathematics, programming, and logical thinking to build quantitative models that drive success in our business. Your problem-solving talents and aptitude for innovation will help define your contributions and enable you to find solutions to a broad range of problems, in a dynamic, fast-paced environment.&nbsp;
Responsibilities
As a strategist on our PWM Risk Strats team, you will work&nbsp;closely with various teams including risk management and fraud strategy.&nbsp;You will combine quantitative techniques and industry knowledge to build best in class models and tools that streamline risk management, detect fraud at scale, enable optimized data-driven business decision making, and optimize profitability.
Responsibilities include:
<ul>
 <li>Developing and deploying ML models for fraud and anomaly detection as well as business workflows enhancement</li>
 <li>Delivering risk metrics and quantitative analytics for financial and non-financial risks across wealth management</li>
 <li>Develop AI-led solutions to improve efficiency and accuracy in risk management.</li>
 <li>Building and maintaining robust and systematic risk management tools and reporting</li>
 <li>Collaborating on the design of new and existing strategies to address clients’ investment goals.</li>
 <li>Developing and maintaining risk management and portfolio analysis tools across multiple asset classes for senior management and portfolio managers.</li>
 <li>Building and maintaining infrastructure of Strategists’ analytical systems.</li>
</ul>
&nbsp;
About Goldman Sachs Wealth Management
Across Wealth Management, Goldman Sachs helps empower clients and customers around the world to reach their financial goals. Our advisor-led wealth management businesses provide financial planning, investment management, banking, and comprehensive advice to a wide range of clients, including ultra-high net worth and high net worth individuals, as well as family offices, foundations and endowments, and corporations and their employees. Our consumer business provides digital solutions for customers to better spend, borrow, invest, and save. Across Wealth Management, our growth is driven by a relentless focus on our people, our clients and customers, and leading-edge technology, data, and design.
Basic Qualifications
<ul>
 <li>Bachelor, Masters or Ph.D. in a quantitative or engineering field, e.g. mathematics, physics, quantitative finance, computational finance, computer science, engineering</li>
 <li>1-3 years of experience in the job offered or related quantitative financial modeling and software development positions</li>
 <li>Programming and mathematical skills are required</li>
 <li>Creativity, problem-solving skills, and ability to communicate complex ideas to a variety of audiences&nbsp;</li>
 <li>A self-starter, should have ability to work independently as well as thrive in a team environment</li>
 <li>Excellent understanding of machine learning techniques and algorithms, such as gradient boosting decision trees, random forests, etc., is a plus</li>
 <li>Experience with building models using common data science toolkits, i.e., Python (Pandas, NumPy, Scikit-learn) and Spark</li>
 <li>Experience with prompt engineering, working with LLM models, and MCP.</li>
 <li>Previous work experience in: Utilizing statistical methods, including time-series and regression analysis; programming in object-oriented languages for efficient model implementations; manipulating data sets using relational databases and SQL</li>
</ul>
Preferred Qualifications
<ul>
 <li>Excellent understanding of machine learning techniques and algorithms, such as gradient boosting decision trees, random forests, etc., is a plus</li>
 <li>Experience with building models using common data science toolkits, i.e., Python (Pandas, NumPy, Scikit-learn) and Spark</li>
 <li>Experience with prompt engineering, working with LLM models, and MCP.</li>
 <li>Previous work experience in: Utilizing statistical methods, including time-series and regression analysis; programming in object-oriented languages for efficient model implementations; manipulating data sets using relational databases and SQL</li>
</ul>
ABOUT GOLDMAN SACHS
At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at&nbsp;<a href="http://gs.com/careers" target="_blank" rel="nofollow">GS.com/careers</a>.&nbsp;
We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more:&nbsp;<a href="https://www.goldmansachs.com/careers/footer/disability-statement.html%C2%A9" target="_blank" rel="nofollow">https://www.goldmansachs.com/careers/footer/disability-statement.html©</a>
The Goldman Sachs Group, Inc., 2023. All rights reserved.
Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.

Asset & Wealth Management - Quantitative Strategist - Analyst - Dallas

Bachelor/Masters/PhD in quantitative/engineering field; 1-3 years in quantitative modeling/software development; Python/Spark experience; ML knowledge.

Yum Crave AI is seeking a Data Scientist (AI/ML Modeling &amp; Algorithms) to support the development and implementation of machine learning models that address operational and business needs. In this role, you will work on moderately complex modeling assignments, applying established data science techniques to deliver scalable AI/ML solutions in partnership with cross-functional teams.This role is ideal for a data scientist who is strengthening their expertise in applied modeling and progressing toward senior-level ownership.<h3>Responsibilities</h3><div>AI / ML Model Development<ul style="list-style-type: disc;"><li>Develop and implement machine learning models using established approaches (regression, classification, forecasting, optimization)</li><li>Translate business and operational requirements into structured modeling problems with guidance from senior team members</li><li>Perform feature engineering, model training, validation, and evaluation using defined best practices</li><li>Contribute to improving existing models and pipelines</li></ul>Experimentation &amp; Model Evaluation<ul style="list-style-type: disc;"><li>Support the design and analysis of experiments (e.g., A/B tests, simulations) under guidance</li><li>Monitor model performance and identify opportunities for improvement</li><li>Apply standard processes to assess model quality, accuracy, and reliability</li></ul>Data &amp; Technical Execution<ul style="list-style-type: disc;"><li>Work with structured and semi-structured datasets to prepare data for modeling</li><li>Write clean, maintainable Python and SQL code</li><li>Partner with Data Engineering and ML Engineering to support model deployment</li></ul>Collaboration &amp; Communication<ul style="list-style-type: disc;"><li>Clearly communicate analytical findings to technical and non-technical stakeholders</li><li>Document assumptions, methodologies, and results</li></ul>Build strong working relationships within the immediate team and cross-functional partners</div><h3>Qualifications</h3><div><ul style="list-style-type: disc;"><li>Bachelor’s or Master’s degree in a quantitative field (e.g., Data Science, Statistics, Computer Science, Engineering, Mathematics)</li><li>2+ years of experience in data science or machine learning</li><li>Experience applying machine learning techniques to real-world problems</li><li>Proficiency in Python and SQL</li><li>Understanding of model evaluation metrics and validation approaches</li></ul>Preferred Qualifications<ul style="list-style-type: disc;"><li>Exposure to deep learning frameworks (e.g., TensorFlow, PyTorch)</li><li>Experience working in cloud environments (AWS, GCP, or Azure)</li><li>Familiarity with experimentation methodologies (A/B testing)</li><li>Experience collaborating with engineering teams on production deployments</li></ul>&nbsp;<p style="-webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255); color: rgb(51, 51, 51); font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, sans-serif; font-size: 14px; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;">Salary Range: 106,600 - 133,200<p style="-webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255); color: rgb(51, 51, 51); font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, sans-serif; font-size: 14px; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;">Benefits: Employees (and their eligible family members) may enroll in the following types of insurance coverage: medical, dental, vision, legal, and accidental death and dismemberment, as well as FSA/HSA (depending on enrolled medical plan). Yum! also provides short-term disability, long-term disability, and life insurance. Employees may enroll in our 401(k) plan. Yum! provides 4 weeks of vacation, paid sick leave, 10 paid holidays, a floating day off, half day Fridays year-round and 2 paid days for volunteer time each calendar year. To learn more about working at Yum! -<a href="https://www.yum.com/wps/portal/yumbrands/Yumbrands/careers#xd_co_f=MmVjOTE4NjktNDg4YS00YzNlLWEwOWYtMjNlNWQ3OTYxNWQz~" target="_blank">Click here.&nbsp;</a><p style="-webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255); color: rgb(51, 51, 51); font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, sans-serif; font-size: 14px; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;">At Yum!, one of our core values is to Believe in ALL People. This means seeing the value in everyone and unlocking their full potential to be their best self. YUM! Brands, Inc. (including its subsidiaries Yum Restaurant Services Group, LLC (“YRSG”) and Yum Connect, LLC (“Yum Digital and Technology”)(collectively, “Yum”) is proud to be an equal opportunity employer and is committed to equity, inclusion, and belonging for all dimensions of diversity. &nbsp;We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other protected characteristic. Yum! is committed to working with and providing reasonable accommodation to applicants with disabilities or special needs.<p style="-webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255); color: rgb(51, 51, 51); font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, sans-serif; font-size: 14px; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;">US Job Seekers/Employees -&nbsp;<a href="https://nam11.safelinks.protection.outlook.com/?url=https://www.dol.gov/agencies/ofccp/posters&amp;data=05|01|Erica.Sherrard@yum.com|3660c56f3ee04ac9a72608dac91373e4|2ba9001dd7f943a3a0986a927ac715ca|0|0|638043382639632622|Unknown|TWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0=|3000|||&amp;sdata=/o9fI4tiDc9ZzKCVeIn8eRmCigUkLI1hvoi21rVwESs=&amp;reserved=0" target="_blank">Click here&nbsp;</a>to view the “Know Your Rights” poster and supplement and the Pay Transparency Policy Statement.</div>

Data Scientist (AI/ML Modeling, Forecasting & Algorithms)

Data Scientist

Bachelor's or Master's in a quantitative field; 2+ years in data science or ML; Python and SQL; ML model development and evaluation; strong communication.

Why USAA?At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the #1 choice for the military community and their families.Embrace a fulfilling career at USAA, where our core values – honesty, integrity, loyalty and service – define how we treat each other and our members. Be part of what truly makes us special and impactful.The OpportunityAs a dedicated Mid-Level Data Scientist, you will be using strategic insights, AI, and automation to empower our insurance business partners in protecting and serving our members. We are seeking a highly collaborative and adaptable technical contributor who will innovate solutions and re-engineer processes to fuel aggressive business growth and exceptional claims experiences. This critical role offers the opportunity to leverage data for strategic insight, solve complex challenges, and deliver game-changing value. If you are passionate about using data to make a real-world difference and help our members build a legacy and protect their most valuable assets, we want to hear from you.Translates business problems into applied statistical, machine learning, simulation, and optimization solutions to inform actionable business insights and drive business value through automation, revenue generation, and expense and risk reduction. In collaboration with engineering partners, delivers solutions at scale, and enables customer-facing applications. Leverages database, cloud, and programming knowledge to build analytical modeling solutions using statistical and machine learning techniques. Collaborates with other data scientists to improve USAA&#39;s tooling, expanding the company&#39;s library of internal packages and applications. Works with model risk management to validate the results and stability of models before being pushed to production at scale.We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position can be based in one of the following locations: San Antonio, TX, Plano, TX or Phoenix, AZ. Relocation assistance is not available for this position.What you&#39;ll do:<ul><li>Gathers, interprets, and manipulates structured and unstructured data to enable advanced analytical solutions for the business.</li><li>Develops scalable, automated solutions using machine learning, simulation, and optimization to deliver business insights and business value.</li><li>Selects the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs.</li><li>Develops and deploys models within the Model Development Control (MDC) and Model Risk Management (MRM) framework.</li><li>Composes technical documents for knowledge persistence, risk management, and technical review audiences.</li><li>Assesses business needs to propose/recommend analytical and modeling projects to add business value.</li><li>Participates in the prioritization of analytics and modeling problems/research efforts with business and analytics leaders.</li><li>Contributes to the development of a robust library of reusable, production-quality algorithms and supporting code, to ensure model development and research efforts are transparent and based on the highest quality data.</li><li>Translates business request(s) into specific analytical questions, executes on the analysis and/or modeling, and then communicates outcomes to non-technical business colleagues with focus on business action and recommendations.</li><li>Works closely with Data Engineering, IT, the business, and other internal stakeholders to deploy production-ready analytical assets that are aligned with the customer&#39;s vision and specifications while being consistent with modeling best practices and model risk management standards.</li><li>Maintains awareness of cutting-edge techniques.</li><li>Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies.</li><li>Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.</li></ul>What you have:<ul><li>Bachelor&#39;s degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative discipline; OR 4 years of experience in statistics, mathematics, quantitative analytics, or related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree.</li><li>4 years of experience in a predictive analytics or data analysis OR Advanced Degree (e.g., Master&#39;s, PhD) in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative discipline and 2 years of experience in predictive analytics or data analysis.</li><li>2 years of experience in training and validating statistical, physical, machine learning, and other advanced analytics models.</li><li>2 years of experience in one or more dynamic scripted language (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models.</li><li>Experience writing code that is easy to follow, well documented, and commented where necessary to explain logic (high code transparency).</li><li>Experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, HQL, NoSQL, etc.</li><li>Experience in working with structured, semi-structured, and unstructured data files such as delimited numeric data files, JSON/XML files, and/or text documents, images, etc.</li><li>Experience in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics.</li><li>Ability to assess regulatory implications and expectations of distinct modeling efforts.</li><li>Experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic regression, discriminant analysis, support vector machines, decision trees, forest models, etc.</li><li>Experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors’ algorithms, DBSCAN, etc.</li></ul><ul><li>Experience communicating analytical and modeling results to non-technical business partners with emphasis on business recommendations and actionable applications of results.</li></ul>What sets you apart:<ul><li>Business Impact-Driven Analytics: Extensive experience partnering with business subject matter experts to translate complex business problems into advanced analytical solutions. This involves critically evaluating approaches, translating technical findings into clear, business-oriented recommendations, and demonstrating a passion for driving the adoption of data-driven strategies that improve processes and create new, automated workflows.</li><li>End-to-End AI/ML Solution Delivery in Regulated Environments: Proven track record of collaborating with data scientists, data engineers, product manager, and IT to deliver AI/ML solutions to business partners. This includes a foundational understanding of Model Risk Management (MRM) and governance principles, essential for operating in highly regulated environments.</li><li>Software Engineering Rigor in Modeling: Demonstrated proficiency in software engineering best practices for data science, such as robust coding standards, package development and scripting, version control, and markdown-based documentation to allow for seamless collaboration with engineering teams for model deployment and productionization. We&#39;re looking for a strong understanding of bringing models from ideation through development and into production, utilizing non-notebook driven workflows for reproducibility. Experience in Python, Domino Data Labs, and Snowflake are preferred.</li><li>Expertise in Insurance and Customer Engagement: Experience in claims and/or marketing within property and casualty insurance, life insurance, health insurance, and/or annuities. This includes proven expertise in using analytics to drive marketing engagement and optimization, enhancing claims experiences, supporting call centers, and enhancing digital workflows and journeys.</li><li>Rigorous Model Validation and Experimentation: Experience in user acceptance testing, pilot testing, experimentation, and A/B testing to evaluate the value delivery of model solutions; experience with Bayesian analysis and/or event-driven simulation model development and their applications in a production environment.</li><li>US Military Experience: Military service or being a military spouse/domestic partner.</li></ul>Compensation range: The salary range for this position is: $114,080.00 - $218,030.00.USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.). Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location.  Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors.The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job. Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs. Additionally, our career path planning and continuing education assists employees with their professional goals. For more details on our outstanding benefits, visit our benefits page on USAAjobs.com.Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. Thus, interested candidates are encouraged to apply the same day they view this posting.  USAA is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Mid-Level Data Scientist

Bachelor's degree in a quantitative field or 4+ years experience; 4 years predictive analytics/data analysis plus 2 years ML; Python/R; SQL; work with structured/unstructured data; model development and collaboration.

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