Senior Manager Analytics

Job Title: Data Science & Analytics Engineer (Pega CDH) Location: [Remote / Vienna, VA] Job Type: Contract Duration: [6+ Months] Job Summary We are seeking a highly skilled Data Science & Analytics Engineer to join our team and drive advanced analytics initiatives within our Pega Customer Decision Hub (CDH) ecosystem. In this role, you will be responsible for developing scalable data retrieval and analysis frameworks, building monitoring solutions for machine learning models, and enabling deeper analytical insights for business stakeholders. You will work closely with cross-functional teams, including Marketing, Operations & Analytics (O&A), Model Development & Strategy Analytics (MDSA), and leadership to ensure data-driven decision-making and model performance excellence. • Looking for: Pega CDH (Customer Decision Hub) experience, preferably with a marketing background. • Additional skills required: Some experience in coding, analytics, data science, Databricks, and Power BI. • Initial responsibilities: The candidate will be doing some coding at the start, specifically using PySpark. • Work model: Open to remote candidates. (Local candidates will be their first preference) Key Responsibilities 1. Data Extraction & Standardization • Develop and maintain a library of required queries/scripts to replicate the CDH customer contextual object in external systems such as Databricks and Azure Synapse (ASL) for deeper analysis. • Standardize the format for executing key data retrieval steps to ensure consistency and usability for the broader team, including: • Interaction-to-outcome attribution (e.g., account opens) • Model data-to-interaction mapping (model performance, predictor performance) • Member profile-to-interaction mapping 1. Notebook Development & Team Enablement • Create reusable notebooks for the broader team to answer specific business questions, including: • Distribution Analysis • Arbitration Analysis • Channel Engagement Analysis • Empower team members with self-service analytics tools and standardized frameworks. 1. Model Performance & Monitoring • Establish baseline KPIs and back-testing approaches for new model-related features (e.g., propensity thresholds). • Develop and maintain ongoing model performance monitoring frameworks. • Support initial model maturity analysis and collaborate with MDSA on code changes and logic enhancements. • Build and maintain a health dashboard for the NBI Program Model, ensuring it is presentation-ready for leadership and broader stakeholders. 1. Operational & Actionable Analytics • Identify and close analytical gaps by standardizing the approach for: • Actionable Monitoring Data: Capture when propensity scores are exceptionally low closer to real-time (within 1 day). • Value Assessment: Detect when actions are not providing value to their intended objectives (acquisition, engagement). • Monitor eligible audience for different actions/treatments, leveraging simulation environments post-live deployment. • Tie interactions back to key Member demographic data for granular analysis, ensuring this process is standardized for all team members. Required Qualifications Education & Experience • Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field (Master’s preferred). • [X]+ years of experience in data science, analytics engineering, or a related role. Technical Skills • Databricks Environment: Proficiency in working within Databricks for data engineering and analytics. • Programming Languages: Strong proficiency in Python/PySpark and SQL. • Pega CDH Experience: Hands-on experience with Pega Customer Decision Hub is strongly preferred. • Data Platforms: Experience with Azure Synapse, Snowflake, or similar cloud data platforms. • Notebooks: Experience creating and maintaining analytical notebooks for team-wide use. Analytical & Business Skills • Proven ability to establish KPIs, back-test models, and monitor model performance. • Experience with attribution modeling, arbitration analysis, and distribution analysis. • Strong communication skills to translate complex technical findings into actionable insights for leadership and non-technical stakeholders. Preferred Qualifications • Experience with model governance and compliance frameworks. • Familiarity with marketing analytics, customer engagement, and acquisition/retention metrics. • Exposure to simulation environments for audience targeting and treatment optimization. Key Competencies • Analytical Rigor: Ability to back-test, monitor, and improve model performance systematically. • Collaboration: Proven ability to work across teams (O&A, MDSA, Marketing, Leadership) to drive alignment and deliver results. • Standardization Mindset: Passion for creating reusable, scalable solutions that empower the broader team. • Proactive Problem-Solving: Ability to identify gaps and develop standardized approaches to close them. Why Join Us? • Opportunity to work on cutting-edge analytics within a leading financial services organization. • Collaborative environment with exposure to cross-functional teams and executive leadership. • Chance to shape the future of customer engagement and model-driven decision-making.