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Strong global brand, popular mid-level data scientist role, Pune metro location, and broad ML requirements increase competition.
Core ML skills are transferable but finance domain preference and regulated context moderately reduce cross-industry fit.
Explicit 6+ years, CS degree and mandatory ML/data engineering skills create strict shortlisting filters.
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Develop Python software to acquire and prepare datasets for machine learning including ETL pipelines, data quality checks, and unit tests.
Research, prototype, and tune machine learning models (supervised, unsupervised, time series) to achieve best out-of-sample performance using ensemble methods and hyper-parameter optimization.
Collaborate with domain experts, internal/external stakeholders and facilitate data science education, presentations, and onboarding new members; may guide other dev teams for production readiness.
6+ years of overall work experience.
Undergraduate or graduate degree in Computer Science with a strong statistical background.
Proficiency in Python and related libraries (numpy, pandas, sklearn), Linux environments, source control; knowledge of distributed ML frameworks (e.g. Keras, TensorFlow) and Azure cloud preferred.
Finance sector experience or coursework and graduate-level Data Science education preferred but not mandatory.
Experienced in independently managing the end-to-end research and prototype development lifecycle in applied data science within complex, regulated environments, preferably finance.
Strong technical acumen in multiple ML algorithm classes and data engineering involving distributed/cloud computing environments.
Effective collaborator with ability to communicate complex technical findings to both technical and non-technical stakeholders, and to support mentorship or coaching activities.