Senior Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Assist in delivering an expanding range of client projects

• Convert clients’ business challenges into comprehensive end-to-end data science workflows

• Collaborate closely with clients to identify data requirements

• Develop data pipelines to collect and transform raw loyalty program data into clean, structured datasets suitable for analysis and modeling

• Design, construct, and assess predictive models

• Make informed decisions regarding feature engineering, methodologies, and trade-offs

• Distill analytical findings into clear narratives for non-technical clients

• Provide data-driven insights to support client business decisions

• Conduct ad hoc analyses and address unique challenges

• Create innovative solutions and develop new analytical methodologies

• Contribute to the advancement of the analytics platform

• Manage the entire data science workflow from data collection to insights

⛳️ Requirements

• Minimum of 5 years of professional experience in data science, data engineering, or a role focused on analytics

• Bachelor’s or master’s degree in mathematics, economics, bioinformatics, statistics, engineering, computer science, actuarial science, or another quantitative discipline

• Proven hands-on experience with Python and/or PySpark for cleaning, transforming, and handling large, complex datasets

• Strong proficiency in Python and/or PySpark

• Solid expertise in SQL

• Capability to build and sustain production-quality analytical workflows

• Advanced skills in Excel

• Ability to align technical work with business objectives

• Familiarity with predictive modeling techniques relevant to actuarial science, data science, or predictive analytics roles

• Proficiency in articulating modeling techniques, assumptions, and results to non-technical stakeholders

• Excellent communication skills

• A growth-oriented mindset

• Capacity to clearly convey modeling techniques, methodologies, assumptions, and results to both technical and non-technical audiences

• An actuarial background, hands-on experience in developing and analyzing P&C actuarial models end-to-end, or ACAS/FCAS qualifications are advantageous

• Demonstrated experience with big data frameworks (e.g., Hadoop, Spark)

• Familiarity with dashboarding/data visualization tools (e.g., Plotly Dash, Power BI)

🏝️ Benefits

• Retirement Plan (401k with employer matching)

• Qualified Small Employer Health Reimbursement Arrangement (QSEHRA)

• Discretionary Paid Time Off (PTO)

• Fully remote work environment