marketing data scientist

Thorne

<div>
 
 
 Department:
 
 Marketing
 
 
 
 Location:
 
 Remote
 
 
 
 Compensation:
 
 $150,000 - $165,000 / year
 
 
 
 
 Description
 
 
 
 
 At Thorne, we work to deliver high-quality, science-backed solutions to empower individuals to take a proactive approach to their well-being. Each day begins with a mission to help others discover and achieve their best health. We count on our team members to challenge and push the boundaries to make that happen. At Thorne, you&rsquo;ll be joining a team of more than 750 passionate individuals committed to our cause of providing superior health solutions at every age and life stage.
 
 
 
 The Marketing Data Scientist will lead modeling and analytics initiatives that improve how we understand, engage, and grow our customer base. This role will focus on building models that uncover insights about customer demographics, behaviors, and preferences to drive more effective marketing strategies.
 
 
 This role will partner closely with marketing, analytics, and product teams to identify opportunities where modeling can improve targeting, customer engagement, and marketing performance. This role will also own and refine the organization&rsquo;s Marketing Mix Model while developing new models that enhance customer segmentation, lifecycle marketing, and product insights.
 
 
 The ideal candidate combines strong statistical and machine learning expertise with the ability to translate analytical findings into clear strategic recommendations for business stakeholders.
 
 
 
 
 
 
 RESPONSIBILITIES
 
 
 
 
 Marketing Mix Modeling &amp; Channel Measurement
 
 <ul>
 <li>
 Own and refine the organization&rsquo;s Marketing Mix Model (MMM), evaluating current methodology and improving model accuracy and interpretability.
 </li>
 <li>
 Translate model outputs into actionable insights that inform marketing investment decisions and channel strategy.
 </li>
 <li>
 Partner with marketing stakeholders to ensure model outputs are effectively incorporated into planning and performance evaluation.
 </li>
 </ul>
 
 
 Customer Segmentation &amp; Behavioral Modeling
 
 <ul>
 <li>
 Develop advanced customer segmentation models that leverage demographic, behavioral, and transactional data to improve targeted marketing strategies.
 </li>
 <li>
 Build models that identify meaningful customer cohorts, lifecycle stages, and engagement patterns.
 </li>
 <li>
 Support marketing teams in operationalizing segmentation frameworks that drive personalized marketing and audience targeting.
 </li>
 </ul>
 
 
 Marketing Engagement &amp; Journey Modeling
 
 <ul>
 <li>
 Analyze customer interaction patterns to identify optimal marketing engagement strategies across the customer lifecycle.
 </li>
 <li>
 Develop models that inform more effective marketing journeys, channel sequencing, and customer touchpoints.
 </li>
 <li>
 Partner with marketing and data teams to enable activation of model outputs through marketing platforms and customer data infrastructure.
 </li>
 </ul>
 
 
 Customer Insights &amp; Sentiment Modeling
 
 <ul>
 <li>
 Build models that help identify emerging customer needs, sentiment trends, and product opportunities.
 </li>
 <li>
 Analyze customer feedback, engagement behavior, and other signals to uncover insights that inform marketing strategy and product development.
 </li>
 <li>
 Provide recommendations on how insights from customer behavior and sentiment can guide new product or feature opportunities.
 </li>
 </ul>
 
 
 Model Development &amp; Innovation
 
 <ul>
 <li>
 Identify new opportunities where statistical or machine learning models can improve marketing effectiveness and customer understanding.
 </li>
 <li>
 Design and build models using modern data science tools and methodologies.
 </li>
 <li>
 Continuously evaluate emerging techniques and determine their applicability to marketing and customer analytics.
 </li>
 </ul>
 
 
 Stakeholder Partnership
 
 <ul>
 <li>
 Partner with marketing channel owners and product teams to identify analytical opportunities that support marketing strategy and customer growth.
 </li>
 <li>
 Present modeling insights and recommendations to marketing leadership and cross-functional stakeholders.
 </li>
 <li>
 Help build a data-driven culture within marketing by translating complex analyses into actionable business insights.
 </li>
 </ul>
 
 
 Vendor &amp; Cross-Functional Collaboration
 
 <ul>
 <li>
 Collaborate with external partners and vendors that support modeling, machine learning engineering, or advanced analytics initiatives.
 </li>
 <li>
 Partner with internal analytics, engineering, and data platform teams to ensure models can be integrated into data infrastructure and marketing activation workflows.
 
 
 
 
 </li>
 </ul>
 
 WHAT YOU NEED
 
 
 
 
 Required Competencies:
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in a quantitative field such as Statistics, Data Science, Mathematics, Economics, Computer Science, Engineering, or a related discipline.
 </li>
 <li>
 4+ years of experience in data science, marketing science, econometrics, or a related quantitative field.
 </li>
 <li>
 Strong experience building statistical or machine learning models using Python or R.
 </li>
 <li>
 Experience developing customer segmentation, clustering, or behavioral models.
 </li>
 <li>
 Strong foundation in statistical techniques such as regression, clustering, classification, and causal analysis.
 </li>
 <li>
 Strong SQL skills and experience working with large datasets in cloud data environments.
 </li>
 <li>
 Ability to communicate complex analytical findings clearly to non-technical stakeholders.
 </li>
 </ul>
 
 Preferred Competencies/Experience:
 
 <ul>
 <li>
 Master&rsquo;s or PhD in Statistics, Data Science, Economics, Applied Mathematics, Computer Science, or a related quantitative field.
 </li>
 <li>
 Experience working with marketing or customer analytics data.
 </li>
 <li>
 Experience building models that support audience targeting, lifecycle marketing, or personalization.
 </li>
 <li>
 Familiarity with marketing technology platforms, customer data platforms (CDPs), or marketing activation tools.
 </li>
 <li>
 Experience collaborating with external modeling or data science vendors.
 </li>
 <li>
 Experience operationalizing models in production or working alongside ML engineering teams.
 
 
 
 
 
 
 
 
 
 </li>
 </ul>
 
 WHAT WE OFFER
 
 
 
 <ul>
 <li>
 Competitive compensation
 </li>
 <li>
 100% company-paid medical, dental, and vision insurance coverage for employees
 </li>
 <li>
 Company-paid short- and long-term disability insurance
 </li>
 <li>
 Company- paid life insurance
 </li>
 <li>
 401k plan with employer matching contributions up to 4%
 </li>
 <li>
 Gym membership reimbursement
 </li>
 <li>
 Monthly allowance of Thorne supplements
 </li>
 <li>
 Paid time off, volunteer time off and holiday leave
 </li>
 <li>
 Training, professional development, and career growth opportunities
 
 
 </li>
 </ul>
 Thorne is the leader in science-backed health and wellness solutions committed to helping individuals live healthier longer. As the top recommended clinical brand by healthcare practitioners, Thorne offers a comprehensive range of products including nutritional supplements and health tests designed to meet the unique needs of individuals at every stage of life. Founded in 1984, Thorne products are formulated with the highest-quality ingredients, supported by clinical research, and rigorously tested to ensure purity, potency, and efficacy. Thorne is trusted by 47,000+ health-care professionals, thousands of professional athletes, more than 100 professional sports teams, multiple U.S. National Teams, and more than five million consumers. For more information, visit Thorne.com.
 
 
 
 THORNE IS AN EQUAL OPPORTUNITY EMPLOYER
 
</div>

Marketing Data Scientist

SoFi

<div>
 
 Employee Applicant Privacy Notice
 
 
 
 
 Who we are:
 
 
 
 Shape a brighter financial future with us.
 
 
 Together with our members, we&rsquo;re changing the way people think about and interact with personal finance.
 
 
 We&rsquo;re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we&rsquo;re at the forefront. We&rsquo;re proud to come to work every day knowing that what we do has a direct impact on people&rsquo;s lives, with our core values guiding us every step of the way.
 
 Join us to invest in yourself, your career, and the financial world.
 
 
 
 
 The role:
 
 
 
 SoFi is seeking a highly motivated Data Scientist to join the Marketing Data Science (MDS) team. The MDS team plays a crucial role in enabling data-driven decisions across SoFi's Marketing organization through robust analytics, modeling, experimentation, and measurement.
 
 
 This exciting new role will be part of the Optimization hub and will support both TV/DV media-specific optimization and broader marketing budget planning, with roughly half of the work focused on media analytics, forecasting, and optimization, and the other half focused on holistic marketing budget forecasting and scenario planning across brand, sponsorships, product marketing, and all marketing channels (TV, DV, DM, social, display etc.).
 
 
 The role is execution-focused, with ownership of recurring analytical deliverables and workflows. The IC2 will work closely with senior data scientists and marketing stakeholders, with a clear growth path toward independently owning forecasting, optimization analyses, and stakeholder partnerships over time.
 
 
 
 What you&rsquo;ll do:
 
 
 
 
 <ul>
 <li>
 Own and maintain recurring dashboards and analytical deliverables that support media performance monitoring and broader marketing spend diagnostics across channels.
 </li>
 <li>
 Partner with Media, Brand Marketing, and Product Marketing to support day-to-day analytics, deep dives, and planning-related questions.
 </li>
 <li>
 Support quarterly and annual marketing forecasts using SoFi&rsquo;s in-house Marketing Mix Modeling (MMM) and related forecasting frameworks.
 </li>
 <li>
 Run MMM pipelines and refreshes, including data preparation, quality checks, model execution, and output validation.
 </li>
 <li>
 Assist in interpreting MMM outputs and translating results into insights that inform media and marketing investment decisions.
 </li>
 <li>
 Support media allocation and optimization analyses (e.g., TV vs. Digital, upper- vs. lower-funnel tradeoffs), including scenario modeling and sensitivity analysis.
 </li>
 <li>
 Contribute to holistic marketing budget optimization and scenario planning across brand, sponsorships, product, and performance marketing investments.
 </li>
 <li>
 Support cross-channel budget tradeoff analyses to evaluate the impact of spend shifts across media types and marketing initiatives.
 </li>
 <li>
 Contribute to ongoing improvement of MMM models and forecasting tools, including feature development, testing, automation, and documentation.
 </li>
 <li>
 Collaborate closely with senior data scientists to improve forecast accuracy, model robustness, and the usability of optimization outputs for stakeholders.
 </li>
 <li>
 Maintain clear documentation of models, assumptions, and analytical workflows to support long-term maintainability.
 
 
 
 </li>
 </ul>
 
 What you&rsquo;ll need:
 
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Statistics, Mathematics, Economics, Engineering, or a related quantitative field.
 </li>
 <li>
 2&ndash;4 years of experience in data science, analytics, or applied modeling roles supporting marketing, media, growth, or product analytics.
 </li>
 <li>
 Strong proficiency in SQL and Python, with experience building analytical workflows and working with large, structured datasets.
 </li>
 <li>
 Experience with forecasting, causal modeling, or Marketing Mix Modeling (MMM), including running model pipelines and supporting model interpretation.
 </li>
 <li>
 Familiarity with marketing performance measurement across a broad range of channels, including upper- and lower-funnel investments.
 </li>
 <li>
 Experience building and maintaining dashboards or recurring analytical deliverables using BI tools (e.g., Tableau or equivalent).
 </li>
 <li>
 Comfort working in a production analytics environment, including data validation, model QA, and ongoing maintenance.
 </li>
 <li>
 Ability to translate analytical results into clear insights for non-technical stakeholders, with support from senior team members.
 </li>
 <li>
 Strong attention to detail, structured problem-solving skills, and comfort working with ambiguous planning questions.
 </li>
 <li>
 Collaborative mindset and ability to work effectively with cross-functional partners across Marketing.
 </li>
 <li>
 Curiosity and motivation to grow toward greater ownership of forecasting, optimization, and stakeholder-facing work over time.
 
 
 
 </li>
 </ul>
 
 Compensation And Benefits
 
 
 
 The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate&rsquo;s experience, skills, and location.
 
 
 To view all of our comprehensive and competitive benefits, visit our
 
 Benefits at SoFi
 
 page!
 
 
 SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.
 
 
 The Company hires the best qualified candidate for the job, without regard to protected characteristics.
 
 
 Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
 
 
 New York applicants: Notice of Employee Rights
 
 
 SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com.
 
 
 Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.
 
 
 
 Internal Employees
 
 
 
 If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.
</div>

Marketing Data Scientist, Optimization

Google

<div>
 
 Minimum qualifications:
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Data Science, Statistics, Computer Science, Mathematics or a related field and 6 years of experience in the job offered or in a Business Data Science-related occupation.
 </li>
 <li>
 Alternatively, will accept a Master&rsquo;s degree in Data Science, Statistics, Computer Science, Mathematics or a related field, and 4 years of experience in the job offered or in a Business Data Science-related occupation.
 </li>
 <li>
 Position requires 4 years of experience in the following:
 </li>
 <ul>
 <li>
 SQL for querying databases and extracting data
 </li>
 <li>
 Data extraction, manipulation, and cleaning for analysis
 </li>
 <li>
 Framing ambiguous business problems into tractable quantitative problems
 </li>
 <li>
 Python or R for statistical analysis and implementing algorithms
 </li>
 <li>
 Presenting and defending data-driven solutions to senior leadership
 
 
 </li>
 </ul>
 </ul>
 
 About The Job
 
 
 
 The US base salary range for this full-time position is $169,550 - $239,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
 
 
 Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .
 
 
 Position reports to the Google New York, New York office and may allow for a hybrid schedule per Google policy.
 
 
 The Global Business Organization (GBO) is the engine that powers Google&rsquo;s full ecosystem of products and services to help customers and partners succeed and grow. GBO includes the commercial arms of Ads sellers, business development teams, and customer services and support, as well as overlay programs that enable coordinated engagement with Google's most complex and important customers and partners.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Collaborate with stakeholders to translate business goals into tractable analytical questions, defining requirements and roadmaps.
 </li>
 <li>
 Lead the gathering, extraction, and validation of data from diverse sources, ensuring quality, security, and confidentiality.
 </li>
 <li>
 Formulate and interpret complex datasets to generate actionable conclusions and provide expert guidance on analytical challenges.
 </li>
 <li>
 Develop key performance metrics and create automated dashboards and tools to monitor solutions and guide product decisions.
 </li>
 <li>
 Drive product strategy by identifying gaps through data analysis, helping teams prioritize work, and influencing business decisions. Implement and scale solutions by writing production-level code, creating reusable documentation, and driving adoption of recommendations.
 
 
 
 </li>
 </ul>
 Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
</div>

Business and Marketing Data Scientist

<div>
 
 Data Scientist
 
 
 Hybrid; Jersey City, NJ
 
 
 Up to $109k + bonus
 
 
 For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits
 
 
 
 
 
 The Data Science team partners with marketing, analytics, and digital optimization teams to develop advanced analytical solutions that improve marketing effectiveness and customer engagement.
 
 
 
 
 
 This role focuses on applying statistical modeling, experimentation, and machine learning techniques to understand customer behavior across the marketing and digital customer journey. Insights generated from this work help guide marketing strategy, customer targeting, and investment decisions.
 
 
 
 
 
 The position operates within a modern analytics environment leveraging Amazon Redshift, AWS SageMaker, and AWS CodeCommit to build scalable analytical workflows and production-ready models.
 
 
 
 
 
 
 
 
 
 Job Description
 
 
 
 
 
 
 We are seeking a Senior Data Scientist with strong statistical expertise to develop analytical frameworks, predictive models, and experimentation strategies that support marketing optimization and customer journey analysis.
 
 
 
 
 
 The role requires a strong understanding of statistical inference, causal analysis, and predictive modeling to help translate business questions into rigorous analytical solutions. The candidate should be comfortable working with large datasets, building scalable models, and communicating analytical insights to cross-functional teams.
 
 
 
 
 
 This position requires collaboration with marketing strategy, digital optimization, and analytics teams to ensure analytical insights are effectively integrated into business decision-making.
 
 
 
 
 
 
 
 
 
 Responsibilities
 
 
 
 
 
 <ul>
 <li>
 Develop statistical and machine learning models to analyze customer behavior across marketing and digital channels.
 </li>
 <li>
 Conduct deep analytical investigations to identify drivers of customer acquisition, engagement, conversion, and retention.
 </li>
 <li>
 Design and evaluate marketing experiments and A/B tests to measure campaign effectiveness and customer impact.
 </li>
 <li>
 Apply causal inference techniques to distinguish correlation from true causal effects in marketing and customer data.
 </li>
 <li>
 Translate business questions into statistical analysis frameworks and modeling approaches.
 </li>
 <li>
 Connect analytical insights to business outcomes including revenue growth, marketing efficiency, and cost optimization.
 </li>
 <li>
 Build scalable analytical pipelines using Python and SQL.
 </li>
 <li>
 Query and analyze large datasets within Amazon Redshift.
 </li>
 <li>
 Develop and deploy predictive models using AWS SageMaker.
 </li>
 <li>
 Maintain version-controlled analytical workflows using AWS CodeCommit.
 </li>
 <li>
 Collaborate with marketing, analytics, and engineering teams to ensure analytical solutions support business strategy and operational decision-making.
 </li>
 <li>
 Present analytical findings and recommendations to technical and non-technical stakeholders.
 </li>
 </ul>
 
 
 
 
 
 
 
 
 Qualifications
 
 
 
 
 
 <ul>
 <li>
 Master&rsquo;s degree in Statistics or a related quantitative discipline such as econometrics, applied mathematics, operations research, or data science.
 </li>
 <li>
 Strong proficiency in Python for statistical analysis and modeling.
 </li>
 <li>
 Strong proficiency in SQL for large-scale data querying.
 </li>
 <li>
 Experience working with large datasets and advanced analytical methods.
 </li>
 </ul>
 
 
 
 
 
 Preferred experience includes:
 
 
 
 
 
 <ul>
 <li>
 Experience in marketing analytics, customer analytics, or digital analytics.
 </li>
 <li>
 Experience designing and evaluating A/B tests and controlled experiments.
 </li>
 <li>
 Knowledge of causal inference methods and experimental design.
 </li>
 <li>
 Experience building production-ready machine learning models.
 </li>
 <li>
 Familiarity with AWS analytics and machine learning tools, including Amazon Redshift and AWS SageMaker.
 </li>
 </ul>
</div>

Data Scientist

<div>
 This role may also be located in our Playa Vista, CA campus.
 
 
 Applicants in the County of Los Angeles: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
 
 
 Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
 
 New York, NY, USA; Chicago, IL, USA; Los Angeles, CA, USA; San Bruno, CA, USA
 
 .
 
 Minimum qualifications:
 
 
 
 <ul>
 <li>
 Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
 </li>
 <li>
 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
 
 
 </li>
 </ul>
 
 Preferred qualifications:
 
 
 
 <ul>
 <li>
 5 years of experience in the consumer tech, media, or entertainment industry.
 </li>
 <li>
 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
 </li>
 <li>
 Experience in causal inference techniques with a proven track record of applying them to solve business problems.
 </li>
 <li>
 Experience with advanced modeling techniques, including Marketing Mix Modeling (MMM), user LTV forecasting, and churn prediction and in e-commerce, retail analytics or two-sided marketplaces.
 </li>
 <li>
 Excellent communication and presentation skills, with a knack for distilling topics into simple, powerful messages.
 
 
 </li>
 </ul>
 
 About the job
 
 In this role, you will join the YouTube Marketing Data Science, Infra and Analytics (DSIA), a analyst team that influences and informs YouTube&rsquo;s marketing and products teams. You will work on projects that drive GTM and brand strategy for YouTube using data to ensure our marketing efforts are efficiently and effectively deployed.
 
 
 As a Business Data Scientist on YouTube Shopping, you will be instrumental in optimizing marketing campaigns across the entire YouTube Shopping creator and viewer life-cycle. You will leverage your expertise in experimental design, data analysis, and machine learning to drive tangible improvements in creator engagement, viewer awareness, and overall platform efficacy.At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun &mdash; and we do it all together.
 
 
 The US base salary range for this full-time position is $138,000-$198,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
 
 
 Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Partner with Growth Marketing and Product teams to analyze and optimize the end-to-end shopper journey, from acquiring new shoppers to driving repeat purchases.
 </li>
 <li>
 Develop user segmentation and propensity models to power personalized marketing campaigns, targeting shoppers with the right product at the right time.
 </li>
 <li>
 Collaborate with engineering and marketing to determine the signals we need to ensure we are connecting creators and viewers with the right offers at the right time.
 </li>
 <li>
 Develop and own the LTV models for YouTube shoppers, providing a critical input for long-term planning and investment.
 </li>
 <li>
 Design incentive programs experiments and optimize life-cycle communications with incentives.
 
 
 
 </li>
 </ul>
 Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
</div>

Business Data Scientist, YouTube Marketing Shopping

Walmart

<div><h2 class="jobSectionHeader">Position Summary...</h2>
As a Principal, Data Scientist, you will lead the development of world‑class marketing analytics that inform and optimize Walmart US Marketing investments. You will operate as a senior individual contributor and thought leader, influencing strategy through advanced analytics and close partnership with Marketing, Merchandising, Finance, and Technology teams. 
 
This is a highly visible role with broad impact across the organization, focused on shaping how marketing channels and business levers work together to drive customer engagement, incremental sales, and long‑term growth.<h2 class="jobSectionHeader">
What you'll do...</h2><ul><li>
Leading the design and development of advanced marketing measurement and optimization models aligned to short‑ and long‑term business objectives</li><li>
Integrating marketing performance insights into a broader understanding of customer engagement and lifetime value</li><li>
Serving as a trusted analytics partner to senior stakeholders, balancing business strategy with analytical rigor</li><li>
Providing thought leadership on advanced analytics opportunities that drive incremental performance and measurable business value</li><li>
Partnering with Data Enablement and Technology teams to define analytics data pipelines, tools, and reporting solutions</li><li>
Collaborating with Marketing, Finance, Tech, and Planning teams to forecast marketing&rsquo;s incremental contribution to sales and traffic</li><li>
Developing tools and training that enable marketers to adopt an analytical mindset in day‑to‑day decision‑making</li><li>
Communicating complex technical concepts clearly and building compelling narratives that influence executive decision‑making</li></ul>
We&rsquo;ll be excited if you bring:
<ul><li>A strong track record of solving complex, large‑scale data science problems and delivering impactful analytics solutions</li><li>
A customer‑first mindset with experience working across multiple business functions</li><li>
Hands‑on experience transforming and automating data within cloud‑based architectures (e.g., Google Cloud Platform)</li><li>
Proven ability to communicate complex quantitative insights to senior leaders and non‑technical audiences</li><li>
Experience partnering effectively with data scientists, data engineers, and cross‑functional stakeholders</li><li>
Curiosity, adaptability, and comfort operating in fast‑paced, ambiguous environments</li><li>
Passion for agile ways of working and continuous improvement</li></ul><h3 class="jobSectionHeader">
Minimum Qualifications</h3><ul><li>
Bachelor&rsquo;s degree in Business, Marketing, Mathematics, Statistics, or a related field (or equivalent experience)</li><li>
7+ years of experience in data analysis or analytics‑driven roles</li><li>
3+ years of experience in Retail, Digital, or eCommerce Analytics</li><li>
2+ years of experience influencing cross‑functional partners across Product, Finance, Operations, or Engineering</li><li>
Strong ownership mindset with excellent communication and organizational skills</li></ul><h3 class="jobSectionHeader">
Preferred Qualifications</h3><ul><li>
PhD in Economics, Statistics, Computer Science, Operations Research, or a related field</li><li>
9+ years of experience in data science, machine learning, or optimization modeling</li><li>
Advanced proficiency in Python, Spark, Scala, or R</li><li>
Extensive experience with open‑source ML frameworks (e.g., Scikit‑Learn, TensorFlow, PyTorch)</li><li>
Experience developing and deploying scalable marketing measurement solutions, including marketing mix modeling and multi‑touch attribution</li><li>
Deep knowledge of supervised and unsupervised modeling techniques, causal inference, and experimentation methodologies</li><li>
Experience leveraging cloud‑based big data technologies and modern data visualization tools</li><li>
Strong understanding of digital marketing channels and advertising technology ecosystems</li><li>
Consulting experience and demonstrated thought leadership with senior business partners</li></ul>
At Walmart, we offer competitive pay as well as performance-based bonus awards and other great benefits for a happier mind, body, and wallet. Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty, and voting. Other benefits include short-term and long-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more. You will also receive PTO and/or PPTO that can be used for vacation, sick leave, holidays, or other purposes. The amount you receive depends on your job classification and length of employment. It will meet or exceed the requirements of paid sick leave laws, where applicable. For information about PTO, see https://one.walmart.com/notices. Live Better U is a Walmart-paid education benefit program for full-time and part-time associates in Walmart and Sam's Club facilities. Programs range from high school completion to bachelor's degrees, including English Language Learning and short-form certificates. Tuition, books, and fees are completely paid for by Walmart.
 
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms.
 
For information about benefits and eligibility, see One.Walmart.
 
San Bruno, California US-08848: The annual salary range for this position is $143,000.00 - $286,000.00
 
Bentonville, Arkansas US-30008: The annual salary range for this position is $110,000.00 - $220,000.00
 
Hoboken, New Jersey US-10279: The annual salary range for this position is $132,000.00 - $264,000.00 Additional compensation includes annual or quarterly performance bonuses. Additional compensation for certain positions may also include :
 
<ul><li>Stock</li></ul>
ㅤ
ㅤ
ㅤ
ㅤ
&lrm;<h2 class="jobSectionHeader">
Minimum Qualifications...</h2>
Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.
Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field. Option 3: 7 years' experience in an analytics or related field.<h2 class="jobSectionHeader">
Preferred Qualifications...</h2>
Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.
Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart&rsquo;s accessibility standards and guidelines for supporting an inclusive culture.<h2 class="jobSectionHeader">
Primary Location...</h2>
850 Cherry Avenue, San Bruno, CA 94066-3031, United States of America
Walmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.</div>

(USA) Principal, Data Scientist

USAA

<div>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 &ndash; honesty, integrity, loyalty and service &ndash; define how we treat each other and our members. Be part of what truly makes us special and impactful.
The Opportunity
The Bank AI/ML team is looking for candidates with backgrounds in model development for credit risk, marketing, or everyday banking.
As a Data Scientist, you will translate 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&rsquo;s tooling, expanding the company&rsquo;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.
This role is remote eligible in the continental U.S. with occasional business travel. However, individuals residing within a 60-mile radius of a USAA office will be expected to work on-site four days per week.
Relocation assistance is available for this position.
What you'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. 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&rsquo;s vision and specifications while being consistent with modeling best practices and model risk management standards.</li><li>
Maintains awareness of cutting-edge techniques. 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&rsquo;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&rsquo;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><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>
Medium or large bank experience.</li><li>
Strong working knowledge of Python and/or SAS.</li><li>
Control partner collaboration experience.</li><li>
Familiar with Model Risk Management, Model Governance, and Regulatory requirements.</li><li>
US military experience through military service or a military spouse/domestic partner.</li></ul>
Compensation range: The salary range for this position is: $114,080 - $218,030.
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.</div>

Data Scientist (Mid-level) - Model Development

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