I&F Decision Sci Practitioner Analyst
On-siteMumbai, Maharashtra, India
Job Summary
Design and build machine learning models for propensity scoring, churn prediction, next-best-action, and loyalty tier migration forecasting. Own the full model lifecycle from problem framing and feature engineering to deployment and performance monitoring. Partner with analysts to productionize models, integrate outputs into CRM journeys, and design global control group frameworks for A/B testing. Translate complex model outputs into actionable audience briefs and campaign recommendations while conducting CLV, churn, and engagement analyses. Build campaign performance dashboards to provide real-time views of marketing effectiveness and lead test-and-learn design to inform future strategy.
Required Qualifications
- 3 to 5 years of experience
- Advanced SQL skills
- Proficiency in Python for machine learning and data science — scikit-learn, XGBoost, LightGBM or equivalent
- Experience building and deploying classification, regression and ranking models at scale
- Strong understanding of customer analytics methodologies: propensity modelling, CLTV, churn prediction, predictive segmentation
- Familiarity with MLOps practices — model monitoring, versioning, lifecycle governance and reproducibility
- Experience working with CRM and marketing data: SFMC event data, CDP profiles, transactional and engagement signals
- Understanding of experimental design, control group methodology and A/B testing statistical frameworks
- Experience with AI/ML-driven personalization and decision engines
- Proficiency in Power BI and/or Tableau for dashboard development
- Hands-on experience with CRM and campaign platforms (Salesforce Marketing Cloud, Adobe Campaign, Braze, or similar)
- Strong knowledge of segmentation methodologies and customer analytics (RFM, CLV, propensity scoring)
- Experience designing campaign measurement frameworks including attribution and incrementality A/B testing, attribution basics and funnel analysis
- Strong communication skills - ability to translate complex model outputs into clear business recommendations
- Experience with agentic AI frameworks and LLM-integrated analytics pipelines
- Familiarity with Salesforce Einstein Analytics and Data Cloud ML capabilities
- Knowledge of Tealium CDP data structures and customer profile attributes
- Certifications in machine learning or cloud ML platforms (AWS SageMaker, GCP Vertex AI or similar)
- 2–4 years in data science, machine learning or advanced analytics and 1+ years in campaign analytics or CRM analytics
- Proven track record building and deploying predictive models in production environments
- Experience in CRM analytics, loyalty analytics, customer lifetime value modelling or marketing science
- Exposure to automobile, airline, retail, FMCG or beauty industry
- Bachelor s or Master s degree in Data Science, Statistics, Computer Science, Mathematics or related field
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