Senior Data Scientist

Job Title: Senior Applied Data Scientist

Experience: 5–7 Years (5+ years relevant experience)

Location: Hyderabad / Pune (Hybrid)

Industry: Product-Based (AI & Decision Intelligence)

About the Role

We are seeking a Senior Applied Data Scientist with 5+ years of experience in Applied Data Science, Decision Science, or Business Analytics to drive high-impact decision-intelligence initiatives. In this role, you will lead end-to-end analytical projects, translating complex business challenges into structured hypotheses, predictive frameworks, and actionable growth recommendations. You will work closely with cross-functional leadership, mentor junior analysts, and build reusable data assets that directly power our enterprise AI decision intelligence platform.

Key Responsibilities

• Analytical Leadership & Delivery: Lead end-to-end applied data science initiatives from problem framing and methodology selection to stakeholder alignment and final execution.
• Exploratory & Diagnostic Analysis: Perform root-cause, cohort, trend, variance, scenario, and sensitivity analysis on large-scale enterprise datasets.
• Decision-Support & Modeling: Develop statistical models, forecasting workflows, market segmentation, pricing/revenue optimization frameworks, and A/B testing methodologies.
• Data Engineering Collaboration: Build reliable SQL queries, Python automation scripts, and reusable data assets; partner with data engineers to establish robust data quality checks and metrics consistency.
• Dashboards & Narrative Reporting: Translate analytical outputs into clear, stakeholder-ready stories and visualizations using tools like Tableau, Power BI, or Looker.
• Mentorship & Standards: Review analytical work for rigor and business value; mentor junior data scientists on SQL, Python, and structured problem-solving.

Required Technical Skills & Qualifications

• Experience: 5–7 years of total experience with 5+ years dedicated to Applied Data Science, Decision Science, Business Analytics, or Quantitative Analytics.
• Education: B.E., B.Tech, M.E., M.Tech, B.Sc., or M.Sc. in Statistics, Mathematics, Economics, Data Science, Computer Science, Engineering, Operations Research, or equivalent.
• Core Technical Stack:
• Advanced SQL for dataset creation, complex joins, and validation.
• Proficiency in Python for data analysis, automation, and statistical computing.
• Experience with visualization platforms (Tableau, Power BI, Looker).
• Statistical Mastery: Deep understanding of descriptive/inferential statistics, probability, sampling, hypothesis testing, regression, time-series forecasting, and optimization frameworks.
• Domain Applications: Hands-on experience designing approaches for pricing, demand forecasting, revenue management, customer segmentation, or operational risk.

Personal Competencies

• High business curiosity with a proven ability to map analytical outputs to practical financial outcomes.
• Strong written and verbal communication skills for presenting complex data to non-technical stakeholders.
• Structured problem-solving mindset with an ownership mentality and high attention to detail.
• Excellent cross-functional leadership, stakeholder management, and team-mentoring abilities.

How to Apply

Interested candidates can send their updated resumes directly to [Confidential Information].