Data Scientist - Decision Analytics

Payactiv is a FinTech company focused on earned wage access and financial services that help workers manage their finances. The Data Scientist on the Decision Analytics team will build end-to-end statistical and machine learning solutions, including forecasting models, decision engines, risk strategies, and analytics, while translating data into actionable business recommendations.

What you'll do:

• Own the end-to-end solution from data exploration and feature engineering through model training, validation, deployment, and performance monitoring
• Develop and evaluate statistical and machine learning models, with clear justification for methodology and model selection
• Write production-quality Python and SQL against multi-million-row datasets, with attention to performance, accuracy, and reliability
• Translate ambiguous business questions into structured analyses and deliver actionable recommendations to stakeholders
• Communicate analytical findings clearly to internal stakeholders, translating technical results into insights that support business decisions
• Collaborate with data engineers in designing, validating, and maintaining ETL processes and data pipelines to ensure integrity, quality, and observability
• Stay on top of emerging technologies in analytics, ML/AI, and cloud computing (familiarity with Snowflake and AWS SageMaker is a strong plus)

What they're looking for:

• Bachelor's or Master's degree in a quantitative discipline – Data Science, Engineering, Statistics, Mathematics, Computer Science, Economics, etc
• 1–3 years of experience in Data Science, Engineering or a closely related role
• Proven proficiency in Python (pandas, NumPy, scikit-learn) and SQL, with experience in data transformation, wrangling, and analysis against multi-million-row datasets
• Working knowledge of statistical modeling and machine learning fundamentals, including model selection trade-offs, data leakage, class imbalance, and validation methodology
• Hands-on experience across a range of modeling approaches, which may include regression and generalized linear models, tree-based and ensemble methods, time series forecasting, clustering, or neural networks
• Solid working knowledge of relational databases — comfortable writing performant queries, optimizing slow ones, and reasoning about schemas, joins, and query plans at production scale
• Demonstrated ability to work independently and manage competing priorities with limited supervision
• Excellent communication skills with the ability to convey complex findings to both technical and non-technical audiences
• A proactive, curious, and detail-oriented mindset with strong problem-solving abilities
• Hands-on experience with business intelligence and visualization tools (Sigma, Tableau, Looker, or Power BI)
• Experience designing, validating, and maintaining ETL processes and data pipelines

Benefits:

• Company sponsored Health, Dental, and Vision insurance
• 401K, traditional, and Roth with a company match
• Tuition Assistance or Tuition Reimbursement
• Unlimited Paid Time off
• Monthly Gym Reimbursement
• Paid time off to volunteer
• Paid Family Leave
• Complimentary office lunches
• Opportunity to grow
• Opportunity to work with a great team committed to making a difference.