Develop and deploy predictive models (classification, regression, clustering, time series) to support investment behavior analysis and member targeting.
Automate data pipelines and modeling workflows for scalable deployment across data channels.
Develop interactive dashboards to visualize key trends and model insights
Apply mathematical optimization to improve portfolio strategy, and campaign effectiveness.
Conduct deep-dive analyses on member behavior, transactions, and product adoption to guide data-driven decisions.
Collaborate with cross-functional teams to align analytics with business objectives.
Present findings clearly to technical and non-technical audiences
Model monitoring and documentation**

Requirements

2-3 years of experience with requisite competencies
Proficient in Python, SQL, PySpark, Power BI (or Tableau)
Hands-on experience with statistics, machine learning, time series forecasting, and mathematical optimization
Strong communication, collaboration and presentation and problem-solving skills
Experience with cloud platforms (e.g., Azure Databricks)
Research skills
Independent judgment
Data storytelling and technical presentation skills
Problem solving and critical thinking
Bachelor's Degree in Computers Science, Engineering, Statistics, Operations Research, Mathematics, or degrees in similar quantitative fields
Desired Qualifications: Master's Degree in Data Science, Statistics, Mathematics, Computer Science, or Engineering
3+ years of experience with requisite competencies

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonSQLPySparkPower BITableaustatisticsmachine learningtime series forecastingmathematical optimizationdata pipelines

Soft Skills

communicationcollaborationpresentationproblem-solvingcritical thinkingindependent judgmentresearch skillsdata storytelling