Senior Data Scientist

Key
Accountabilities

•    Lead development
of high-impact predictive and prescriptive models across multiple domains
(advanced segmentation, personalization, pricing, forecasting, advanced
measurement)
•    Design and oversee complex experiments,
including A/B and multivariate and tests
•    Drive
uplift modeling and long-term value prediction to optimize targeting
and offers
•    Research/adapt methods for hard problems;
lead PoCs; scale viable solutions
•    Partner
with business leaders to identify high-value opportunities for predictive model
deployment
•    Co-design MLOps (feature store,
experimentation, monitoring) with DE/P&T; ensure interoperability &
governance
•    Apply causal inference techniques
for marketing and product measurement.
•    Publish
technical best practices and reusable
frameworks

Education

Bachelor’s or Master’s
in a quantitative field (ex: mathematics, statistics, data science) or
an equivalent combination of education and work related
experience

Experience

5-8 years of relevant
work experience in Data Science with business-facing impact delivery
  

Technical Skills
and Knowledge

•    Strong SQL (advanced
queries, stored procs, performance tuning) and Python programming
skills
•    Advanced SQL, Python, and ML and LLM
frameworks (scikit-learn, XGBoost, TensorFlow, PyTorch,
Gemini)
•    Proficiency deploying models in cloud
environments (GCP - BigQueryML & Vertex AI, AWS
SageMaker)
•    Proficiency in causal inference,
optimization algorithms, and advanced experiment
design
•    Expert in GCP/Vertex AI and MLOps
orchestration tools
•    Advanced model governance
and performance monitoring skills
•    Strong grasp
of business impact modeling (ROI, LTV,
incrementality)
•    Independent problem solver
with strong critical thinking skills and business
acumen
•    Strong statistical modeling (logistic/linear
regression, time series, propensity
modeling)
•    Experimental design (A/B,
multivariate)
•    Feature engineering best practices