Predictive Analytics Analyst

Must Have:

• Practical use of tools (Python SQL Databricks etc.)
• Experience with Power BI and SQL
• Knowledge of data pipelines and enterprise data environments
• Familiarity with Azure or comparable cloud platforms
• Implementing and managing Google Analytics tracking codes and Google Tag Manager.

Description

Responsibilities

• Support predictive and advance analytics. Running of advanced analytic techniques including but not limited to multivariate regressions discrete choice modeling conjoint analysis MaxdDiff structural equation modeling time-series/panel data methods path analysis factor analysis or survival analysis. Interpretation and visualization of results.

General Skills

• Experience with Python R mongo Hadoop or SQL SPSS Stata SAS R or similar statistical package capabilities Experience with econometric modeling such as forecasting and time series Experience with statistical software systems performing analysis and working with outcome oriented data Experience with statistical analysis with advanced data management and statistical programming Experience with data visualization Experience in the implementation and coding of algorithms

Experience and Skill Set Requirements

1. Predictive Analytics & Modeling Expertise 25%

• Depth of experience with statistical modeling and predictive techniques
• Application of methods (forecasting segmentation classification etc.)
• Practical use of tools (Python SQL Databricks etc.)
• Ability to apply methods to real-world business problems

2. Data Management & Technical Proficiency 20%

• Experience working with large complex datasets
• Knowledge of data pipelines and enterprise data environments
• Familiarity with Azure or comparable cloud platforms
• Data preparation integration and quality assurance practices

3. Insight Generation & Business Impact 20%

• Ability to translate data into actionable insights
• Demonstrated influence on decision-making
• Experience defining KPIs and measurement frameworks
• Clarity and relevance of analytical outputs

4. Visualization & Communication 15%

• Effectiveness of dashboards and reporting (Power BI or equivalent)
• Ability to communicate complex concepts simply
• Stakeholder engagement and storytelling capability
• Tailoring insights for technical vs. non-technical audiences

5. Collaboration & Delivery 10%

• Experience in cross-functional and agile teams
• Ability to partner with business and technical stakeholders
• Contribution to team outcomes and delivery timelines
• Adaptability in fast-paced delivery environments

6. Leadership & Mentorship 10%

• Experience mentoring or coaching analysts
• Providing technical guidance and standards
• Driving best practices in analytics and data usage
• Contributing to team capability development