Build scalable processes for cleaning, aggregating, and loading data. Contribute to project planning, and assist the team with estimations, timelines, and prioritization. Assists in developing the analytical roadmap, data, and technology strategy. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, physical or mental disability, sexual orientation, marital status, military or veteran status, gender identity and expression, genetic information, or any other factor protected by law. We are committed to creating a diverse and welcoming workplace that includes partners with diverse backgrounds and experiences. We believe that enables us to better meet our mission and values while serving customers throughout our global communities. People of color, women, LGBTQIA+, veterans and persons with disabilities are encouraged to apply. Qualified applicants with criminal histories will be considered for employment in a manner consistent with all federal state and local ordinances. Minimum of 5+ years of industry experience in data and analytics work Strong problem-solving skills with the ability to influence leadership teams at different levels Significant experience working with predictive and statistical modeling, machine learning, and strong expertise in all phases of the modeling pipeline Strong SQL, databases, and ETL / ELT skills required including cleaning and managing data. Advanced competency and expertise in Python, R, or some combination Demonstrated track record of delivering AI/ML models into production with measurable business impact, including expertise in evaluation techniques (A/B testing, lift analysis) and model governance. Experience working with distributed data processing frameworks such as Spark and Databricks, and languages such as Java, PySpark, or Scala Strong collaboration instincts - desire & ability to work with partners to achieve the best outcome for the business. The role requires effective communication with colleagues, stakeholders, and leaders from diverse backgrounds. Proven ability to manage multiple, time-sensitive projects and competing priorities simultaneously to drive projects to completion with minimal guidance and high attention to details. Experience building personalization and recommendation systems (e.g., collaborative filtering, content-based, or hybrid approaches) for digital platforms or mobile apps. Familiarity with ranking algorithms, reinforcement learning, and contextual bandits for optimizing customer experiences. Hands-on experience with model deployment in production environments, including monitoring, retraining, and performance optimization at scale. Strong understanding of offline and online evaluation techniques for recommendation systems (e.g., precision/recall, NDCG, A/B testing). Knowledge of feature engineering for behavioral and transactional data, and experience leveraging real-time data streams for model updates. Partners have access to short-term and long-term disability, paid parental leave, family expansion reimbursement, paid vacation from date of hire*, sick time (accrued at 1 hour for every 25 hours worked), eight paid holidays, and two personal days per year. You will also have access to backup care and DACA reimbursement. This list is subject to change depending on collective bargaining in locations where partners have a certified bargaining representative. If you are working in CA, CO, IL, LA, ME, MA, NE, ND or RI, you will accrue vacation up to a maximum of 120 hours (190 in CA) for roles below director and 200 hours (316 in CA) for roles at director or above. For roles in other states, you will be granted vacation time starting at 120 hours annually for roles below director and 200 hours annually for roles director and above. The actual base pay offered to the successful candidate will be based on multiple factors, including but not limited to job-related knowledge/skills, experience, geographical location, and internal equity. We believe we do our best work when we're together, which is why we're onsite four days a week.