Senior Data Scientist / Lead Data Scientist - Causal Modeling

Tredence

3 - 8 years

25 - 40 Lacs

pune gurugram bengaluru

Posted:1 week ago| Platform:

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Skills Required

causal modeling data scientist python predictive modeling natural language processing machine learning deep learning sql random forest data science linear regression classification statistical modeling machine learning algorithms

Work Mode

Hybrid

Job Type

Full Time

Job Description

About the Role

Data Scientist /Sr Data Scientist / Lead Data Scientist with expertise in Causal Modeling

Key Responsibilities

Design and implement
causal inference frameworks
to measure the true impact of business initiatives, marketing campaigns, and product interventions.
Apply methods such as
propensity score matching, instrumental variables, difference-in-differences, regression discontinuity, uplift modeling, and causal graphs
.
Build and validate robust statistical and machine learning models to support experimentation (A/B testing, quasi-experiments).
Partner with cross-functional teams (product, marketing, operations, data engineering) to define problems, frame hypotheses, and deliver actionable insights.
Develop scalable analytical pipelines and dashboards for causal impact monitoring.
Stay up to date with advances in
econometrics, Bayesian methods, and causal ML techniques
.

Required Skills & Qualifications

Masters or PhD in
Statistics, Econometrics, Computer Science, Mathematics, Economics, or a related field
.
3–10 years of experience as a
Data Scientist / Quantitative Researcher / Econometrician
.
Strong knowledge of
causal inference methods and experimental design
.
Proficiency in
Python / R / SQL
for data manipulation, statistical modeling, and visualization.
Experience with
ML frameworks
(scikit-learn, PyTorch, TensorFlow) is a plus.
Strong analytical mindset with the ability to translate complex results into clear business recommendations.

Good to Have

Experience in
forecasting, recommendation systems, or optimization
.
Exposure to
big data tools
(Spark, Snowflake, Databricks, etc.).
Publications or applied research in causal inference or related fields.

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