Data Scientist

Role Overview

• Build and Deploy Analytical Models
• Design, develop, and validate predictive models — forecasting, classification, regression, and segmentation — with rigorous diagnostics and clear documentation
• Conduct A/B testing and causal analyses to support experimentation programs and measure the impact of client initiatives
• Develop optimization solutions (linear, mixed-integer, multi-objective) and ensure models are production-ready with monitoring in place
• Use Databricks for large-scale data processing and machine learning workflows, integrating data from diverse sources across complex client environments
• Monitor and validate data flows, develop data quality reporting, and perform root-cause analysis when issues surface
• Collaborate with data engineering teams on MLOps practices — MLflow pipelines, model deployment, lifecycle management, and version control via Git/GitLab
• Execute advanced analyses, synthesize findings, and build executive-ready presentations and visualizations using Tableau and Power BI
• Develop new metrics and KPI reports that give clients and internal stakeholders a clearer view of business performance
• Communicate effectively with both business and technical audiences — adapting your framing to the room
• Work with business partners and data engineering teams to elicit requirements, define business rules, and translate client needs into technical specifications
• Contribute to project meetings to align on scope, timelines, and analytical approach across multi-member engagements
• Test database changes prior to release and ensure data designs align with defined standards and governance requirements
• Apply data governance, privacy, and compliance standards consistently across analytical work
• Document models, processes, and business rules clearly enough that others can reproduce, validate, and build on your work

Requirements

• Bachelor's degree in Computer Science, MIS, Statistics, Mathematics, Marketing Research, or a related quantitative field — or equivalent practical experience
• 2–5+ years of hands-on analytics experience including predictive modeling, A/B testing, and optimization
• Advanced SQL and Python for querying, manipulating, and interpreting data from databases and data warehouses
• Hands-on experience with Databricks for large-scale data processing and machine learning workflows
• Proficiency with Tableau and/or Power BI for analysis and stakeholder communication
• Experience with Git/GitLab for version control and collaborative development
• Strong Excel and PowerPoint skills
• Proven ability to present analytical findings to management and partner effectively with both business and technical stakeholders
• Understanding of data governance, privacy, and compliance standards

Tech Stack

• Python
• SQL
• Tableau

Benefits

• medical, dental, and vision coverage
• 401(k) retirement plan
• paid holidays
• Flexible Time Off (FTO)
• additional programs focused on wellness, financial security, and professional growth