Data science specialist

Job Locations Available- Bangalore, Hyderabad, Gurgaon, Mumbai & Pune

You will be responsible for translating complex data and models into clear, actionable marketing recommendations. You will work across data science, product, and engineering teams to deliver solutions in modelling pipelining, deployment and implementation, with a focus on accuracy, explainability and scalability.

A successful candidate will have strong analytical skills, be passionate towards resolving complex problems, building scalable and stable solutions and open for technical challenges. The ideal candidate will bring new knowledge and experience to the team. As a subject matter expert, you will be combining your professional experience and an intrinsic desire for problem solving.

Interpret and communicate key modeling concepts, including carryover, saturation, marginal returns, incrementality, and investment-response relationships in a marketing context Integrate media, audience, customer, transaction, and outcome data to strengthen marketing measurement and decision quality Calibrate model outputs using lift studies, experiments, incrementality testing, and other sources of causal evidence Build reproducible analytical workflows in Python or R with thorough testing, and governance. Partner with product and engineering teams to productionize analytical methods and support innovation Present recommendations, assumptions, limitations, and trade-offs clearly to both technical and business stakeholders

What we’re looking for –

8+ years of experience in econometrics, marketing science, marketing mix modeling, optimization, decision science, or a related analytical discipline. Bachelor’s or Master’s degree in Data Science, Statistics, Econometrics, Mathematics, Operations Research, Engineering, Computer Science, or a related quantitative field. Expertise in Bayesian and frequentist MMM methodologies, including adstock, saturation, carryover, elasticity, and response curve modeling. Advanced proficiency in Python or R for data preparation, statistical analysis, and scalable analytical workflows. Excellent communication skills, with the ability to explain complex analytical concepts to non-technical business stakeholders and executive leadership

Technical Skills-

Strong Expertise in either of the following programming languages Python (pandas, numpy, Sci Py, scikit-learn) R (rstan, glm, forecast, lm, dplyr, tidyverse, data.table) Bayesian modeling frameworks (Py MC, Stan, brms, rstanarm) Model diagnostics, fit assessment, and validation frameworks

Nice to have- Experience building decision-support tools or AI-enabled analytical workflows. Proficiency in SQL Managed teams of analysts

You will fit right in if you have – Think beyond model outputs and focus on business impact. Balance analytical rigor with practical decision-making. Hold high standards for accuracy, reproducibility, governance, and traceability. Enjoy working across data science, engineering, product, and business teams. Can move confidently between technical validation and executive-level communication.