Data Scientist

Job Description
We are seeking a Data Scientist to work on product, customer, and business data for a scalable B2B SaaS platform.
The role focuses on transforming large volumes of structured and semi-structured data into actionable insights, predictive models, and experimentation frameworks that directly influence product decisions, customer retention, and revenue growth.
This position is best suited for candidates with prior experience in B2B SaaS or product-led environments, where data is embedded into daily decision-making.

Key Responsibilities
Analyze  product usage, customer behavior, and transactional data  to identify trends, risks, and growth opportunities
Build and deploy  statistical and machine learning models  for:
Customer churn prediction
Retention and engagement analysis
Usage forecasting and demand modeling
Design, execute, and evaluate  A/B tests and experiments  for product and growth initiatives
Collaborate with  Product Managers, Engineering, Marketing, and Business teams  to define data-driven strategies
Develop dashboards and reports tracking  SaaS metrics  such as activation, retention, churn, LTV, and conversion funnels
Ensure data accuracy, quality checks, and monitoring for analytics pipelines
Communicate insights clearly to technical and non-technical stakeholders
Qualifications
3+ years  of experience as a  Data Scientist  in a  B2B SaaS or product-based company
Strong proficiency in  Python  (Pandas, Num Py, Scikit-learn)
Advanced  SQL  skills with experience querying large datasets
Solid foundation in  statistics, probability, and machine learning
Experience working with  SaaS business metrics  (churn, retention, cohorts, funnel analysis)

Experience with  cloud platforms  (AWS, GCP, or Azure)
Ability to translate business problems into data science solutions