Data Scientist – Analytics & Prediction

Experience: 5–6 Years

Location: (Hybrid / Remote / Onsite)

Employment Type: Full-time

Role Overview

We are seeking a high-impact Senior Data Scientist with deep expertise in statistics, data analytics, and predictive modeling . This role is analytics-first and outcome-driven, requiring strong ownership of data interpretation, forecasting, and decision support . The ideal candidate can independently solve complex business problems using statistical rigor and build reliable prediction models. Exposure to machine learning and GenAI (RAG) is a strong advantage.

Core Responsibilities

• Own end-to-end analytics and prediction workflows from problem framing to business recommendations
• Perform deep statistical analysis to identify trends, correlations, and causal drivers
• Build, validate, and maintain predictive and forecasting models (time-series, regression-based, multivariate)
• Apply inferential statistics (hypothesis testing, confidence intervals, variance analysis) to support decisions
• Conduct EDA, feature engineering, and data preprocessing for high-quality predictions
• Translate ambiguous business questions into quantifiable analytical and predictive frameworks
• Deliver clear, data-backed insights to senior leadership with strong storytelling
• Ensure model accuracy, stability, and explainability over time

Must-Have Skills (Non-Negotiable)

• 5–6 years of hands-on experience in Data Science / Advanced Analytics
• Strong mastery of Statistics
• Descriptive & inferential statistics
• Regression analysis & Probability distributions
• Hypothesis testing
• Proven experience in Data Prediction & Forecasting
• Time-series analysis (trend, seasonality)
• KPI, demand, revenue, or operational prediction
• Advanced Python skills (Pandas, NumPy, Statsmodels, Scikit-learn)
• Strong SQL for complex analytical queries and data validation
• Ability to independently drive analytical projects and influence decisions

Strong Good-to-Have (ML & GenAI Exposure)

• Experience with machine learning models (classification, clustering, ensemble methods)
• Understanding of model evaluation, bias, and explainability
• Exposure to LLMs and RAG architectures , including:
• Embeddings and semantic search
• Vector databases (FAISS, Pinecone, Chroma)
• LangChain / LlamaIndex frameworks
• Experience integrating analytics outputs with AI-driven applications
• Cloud-based data & analytics environments (AWS / Azure)

Visualization & Communication

• Experience creating executive-level dashboards and analytical reports
• Strong data storytelling skills for non-technical stakeholders
• Ability to explain statistical and predictive results clearly and confidently

Education

• Bachelor’s or Master’s degree in Statistics, Mathematics, Data Science, Computer Science

What Sets This Role Apart

• Analytics and prediction are core responsibilities , not support functions
• High ownership and visibility with leadership
• Opportunity to extend traditional analytics into ML and GenAI (RAG) use cases
• Work on real, high-impact business problems