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Protocol Intelligence
Data-driven signals on your job's competitivenessMetro location, mid-level experience and a common data title create moderate candidate competition.
Core ML skills are transferable but finance domain and SageMaker production experience add moderate specificity.
Explicit 5–7 years plus mandatory ML, Python, SageMaker and Redshift/Snowflake skills increase screening strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Lead end-to-end data science projects including exploratory data analysis, building, validating, deploying, and monitoring machine learning models.
Manage intake process, conduct A/B testing, sales funnel analysis, and provide actionable insights using Python.
Partner with senior stakeholders to translate ambiguous business problems into clear data science questions and solutions.
Minimum Requirements
5–7 years of hands-on experience in data science/applied machine learning.
Proficiency in Python (pandas, numpy, scikit-learn) and SQL.
Experience with AWS SageMaker, Redshift and/or Snowflake, and S3 for handling large-scale data and model deployment.
Work location: Gurgaon office with at least 3 days in-office attendance per week; additional in-office expectations may apply.
Ideal Candidate Profile
Strong data science foundation with experience taking models from concept to production and optimization over time.
Skilled in interpreting complex data to solve real business problems, able to challenge assumptions and validate results.
Familiarity with advanced tools and techniques including exploratory data analysis, machine learning modeling, and potentially generative AI, but core data science skills prioritized.