DESIGNATION: DATA SCIENTIST - Marketing
Job Summary
This is NOT a traditional MIS, reporting, dashboarding, or Marketing Analyst role. We are looking for someone who can turn complex business problems into predictive, ML, and AI-driven solutions.
Key Responsibilities
Data Science, ML & Customer Analytics
- Build, train, validate, and optimize ML models for lead scoring, conversion prediction, propensity, segmentation, churn, retention, and CLV/LTV.
- Apply regression, classification, clustering, forecasting, feature engineering, statistical modeling, and other advanced analytical techniques.
- Explore large and complex datasets to identify customer behaviors, patterns, trends, and growth opportunities.
- Develop data-driven solutions to improve customer acquisition, engagement, conversion, and retention.
Marketing Analytics & Optimization
- Analyze marketing channels, campaigns, customer journeys, and acquisition funnels to identify performance drivers.
- Develop and improve Marketing Mix Modeling (MMM), Multi-Touch Attribution (MTA), attribution, and incrementality approaches.
- Design and analyze A/B tests and controlled experiments to measure campaign and business impact.
- Translate analytical findings into actionable recommendations for marketing and business teams.
AI & Generative AI
- Identify opportunities to apply AI and Generative AI to marketing, customer intelligence, personalization, and automation.
- Develop solutions using LLMs, NLP, embeddings, RAG, personalization, and recommendation techniques.
- Work with structured and unstructured data,
- Build AI/ML proof-of-concepts and collaborate with technology teams to move successful solutions toward implementation.
Data & Technology
- Work with large datasets from CRM, marketing platforms, digital channels, mortgage systems, customer databases, and market sources. • Use Advanced SQL and Databricks / Apache Spark for data extraction, transformation, analysis, and feature development.
- Develop scalable data science workflows using modern data and ML platforms.
- Communicate model results, insights, assumptions, and business impact clearly to technical and non-technical stakeholders.
REQUIRED SKILLS
Core Technical Skills
- Strong hands-on experience with Python and Advanced SQL
- Strong understanding of Machine Learning & Predictive Modeling
- Statistics & Statistical Modeling
- Model Development, Validation & Evaluation
- Exploratory Data Analysis (EDA) & Feature Engineering
- A/B Testing & Experimentation
- Experience working with large and complex datasets
- Hands-on experience with Databricks / Apache Spark Preferred
- Pandas, NumPy, Scikit-learn
- TensorFlow / PyTorch
- Generative AI, LLMs & NLP
- MLOps / Model Deployment
- Cloud-based data and ML platforms
- Experience with modern data engineering and ML workflows
Good to Have
- Azure DevOps experience
- Exposure to CI/CD and ML model deployment workflows
- Experience working within Azure-based data and AI environments.
WHAT WE'RE LOOKING FOR
The ideal candidate is a hands-on Data Scientist, not a reporting analyst, who can:
- Convert ambiguous marketing/business problems into Data Science, ML, or AI solutions.
- Work independently with large, raw, and complex datasets.
- Build and evaluate models rather than simply consume reports.
- Apply statistical thinking and experimentation to validate hypotheses. • Understand customer acquisition, conversion, retention, segmentation, attribution, and LTV.
- Connect technical analysis with measurable business outcomes.
- Communicate effectively with both technical and business stakeholders.
- Thrive in a fast-paced, high-growth startup environment.
EXPERIENCE & EDUCATION
- 3-6 years of relevant experience in Data Science, Marketing Data Science, Customer Analytics, Machine Learning, Growth Analytics, or Advanced Analytics.
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, AI, Economics, or a related quantitative field.
- Demonstrated experience delivering real-world ML, AI, predictive analytics, or advanced marketing analytics projects.
Location
Working Conditions
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