Senior Data Scientist

Lifesight; Karnataka; On-site; INR 2,000,000 - 4,000,000; Full time

Benefits offered by this job

Health insurance

Breakfast daily

Friday team lunch

Unlimited coffee, tea & snacks

Job summary

Lifesight, a fast-growing SaaS company, is seeking a senior data scientist to advance measurement models and marketing insights. You will develop regression-based frameworks, causal inference methods, and production-ready pipelines that scale across campaigns and channels.

You will work with product, engineering, and marketing science teams, publish methodological papers, and mentor junior data scientists while applying AI techniques to drive performance and ROI for customers worldwide.

Qualifications

• Master’s or PhD in a quantitative field such as CS, statistics, mathematics, econometrics.
• 5+ years of experience in data science or applied statistics, preferably in marketing analytics.
• Strong expertise in causal inference techniques and marketing measurement.

Responsibilities

• Develop regression-based frameworks to measure channel and campaign ROI.
• Solve complex modeling problems including time-varying coefficients and GAMs.
• Research causal inference, Bayesian modeling, and time-series forecasting.
• Design parameter-recovery studies, simulations, and robustness checks.
• Design and analyze A/B tests and geo-experiments to drive insights.
• Collaborate with product, engineering, and marketing science teams to productionize models.
• Contribute to internal research and author technical documents.
• Mentor junior data scientists and promote methodological rigor.

Skills

Causal inference

Marketing science

Regression modeling

Python

R

SQL

A/B testing

Experiment design

Communication

Education

Master’s or PhD in quantitative field

Tools

SQL

Cloud platforms

Job description

Lifesight is a fast-growing SaaS company focused on helping businesses leverage data & AI to improve customer acquisition and retention. We have a team of 130 serving 300+ customers across 5 offices in the US, Singapore, India, Australia, and the UK. Our mission is to make it easy for non-technical marketers to leverage advanced data activation and marketing measurement tools that are powered by AI, to improve their

performance and achieve their KPIs. Our product is being adopted rapidly globally and we need the best people onboard the team to accelerate our growth.

Key Responsibilities

• Develop, validate, and deploy advanced regression-based frameworks to measure channel and campaign ROI.
• Solve complex modeling problems, including interaction effects, mediation effects, nonlinear relationships, spline- and GAM-based models, hierarchical structures, and time-varying coefficients.
• Research, adapt, and implement methods from academic and industry literature in causal inference, Bayesian modeling, marketing science, experimentation, and time-series forecasting.
• Design and conduct parameter-recovery studies, simulation exercises, sensitivity analyses, and other evaluation frameworks to assess model identifiability, robustness, and reliability.
• Design and analyze A/B tests, multivariate experiments, geo-experiments, and other causal studies to generate actionable business insights.
• Collaborate with product, engineering, and marketing science teams to understand business needs, translate them into technical requirements, and integrate measurement models into scalable production systems.
• Contribute to internal research initiatives and author technical papers, white papers, and methodological documentation that communicate the organization’s scientific work.
• Participate actively in regular Scientific Council meetings, collaborating with academic advisers and internal research teams to review methodologies, challenge assumptions, and shape the research agenda.
• Continuously evaluate and apply relevant AI, machine learning, and statistical techniques to improve the quality, scalability, and differentiation of the measurement platform.
• Establish and promote best practices in data science, causal inference, experimentation, model evaluation, and statistical rigor across the organization.
• Mentor junior data scientists and contribute to a culture of continuous learning, scientific curiosity, and methodological innovation.

Skills

• Master’s or PhD in Computer Science, Statistics, Mathematics, Econometrics, or a related quantitative field.
• Strong expertise in causal inference techniques, including difference-in-differences, synthetic control, instrumental variables, causal graphs, mediation analysis, and Bayesian causal modeling.
• Deep understanding of marketing science and measurement, including marketing mix modeling, incrementality testing, attribution, customer lifetime value prediction, and marketing experimentation.
• Proven track record in building complex regression-based models, including hierarchical or multilevel models, regularized regression, Bayesian regression, and time-varying models.
• Ability to connect causal inference and statistical modeling approaches to practical marketing decisions such as budget allocation, channel optimization, customer acquisition, retention, and long-term value creation.
• Hands-on experience with experimentation design, A/B testing, geo-experiments, and uplift modeling.
• Proficiency in Python or R, SQL, and cloud-based data platforms.
• Experience deploying models into production and working with large-scale data pipelines.
• Ability to read, interpret, and translate academic research papers into practical, scalable implementations.
• Excellent communication skills, with the ability to explain complex models, assumptions, limitations, and results to both technical and business stakeholders.

Experience

• 5+ years of experience in data science or applied statistics, preferably in marketing analytics.

Here’s what you can expect

Early impact – Help shape the tech stack and build products from the ground up.

Agile culture – Small teams, zero bureaucracy.

Great benefits – Competitive pay, health insurance, daily breakfast, Friday team lunch, Fun O’Clock Fridays, and unlimited coffee, tea & snacks.

How to Apply

If this sounds like you, apply now at [[e-mail] ]. We’d love to hear from you!