Back
Mid-level metro data scientist role with broad requirements and generalist title increases candidate competition.
Skills are transferable across industries but customer-analytics domain expertise preferred, yielding medium sensitivity.
Mandatory 3+ years, required Python/SQL and domain experience enforce strict filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Apply machine learning and statistical modeling to segment customers by value and analyze customer lifetime value and behavior transitions.
Develop and validate models including causal inference and next-best-action recommendations to drive customer engagement strategies.
Collaborate across technical and business teams to translate complex data analyses into actionable business insights in a dynamic client environment.
3+ years of hands-on experience in Data Science / Machine Learning.
Proficiency in Python programming and strong SQL skills for handling large datasets.
Experience developing and applying predictive modeling, feature engineering, and customer/behavioral analytics models.
Work Experience Required: Minimum 3 years in relevant data science roles; notice period: Not explicitly mentioned in the JD.
Experienced in customer analytics, including customer segmentation, lifetime value modeling, and causal/experiment-based analysis.
Skilled at connecting technical modeling outputs to business outcomes and communicating insights clearly to diverse stakeholders.
Comfortable operating in ambiguous, evolving client environments, proactively identifying opportunities and adapting analytical approaches accordingly.