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Strong Tier-1 brand, mid-level popular ML/DS role, metro locations, and broad tech requirements drive high competition.
Medium — core ML/AI skills transfer across industries, but platform and domain-specific experience influence fit.
Explicit 3–6 years requirement plus mandatory ML, PySpark, cloud and deployment skills make filters strict.
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Deliver high-quality AI and Data Science solutions across the software development lifecycle including design, coding, deployment, and defect resolution.
Collaborate with multidisciplinary teams including Data Engineers, ML/AI Engineers, and DevOps to implement end-to-end large-scale Data Science and Machine Learning projects.
Drive process improvements and automation initiatives to increase operational efficiency and project outcomes while engaging in Agile practices and mentoring junior team members as needed.
3-6 years of hands-on experience in Data Science, Machine Learning, and Statistical Modeling.
Proficiency in Python, PySpark, SQL and ML libraries such as Numpy, Pandas, Scikit-learn.
Experience with Docker, GIT, Tableau or PowerBI; familiarity with Databricks, Snowflake, and cloud platforms (AWS/Azure/GCP/NVIDIA).
Bachelor’s degree or equivalent in BE/B.Tech/M.C.A./M.Sc (CS) from an accredited university.
Experienced in delivering multi-industry, large-scale Data Science/ML projects independently and collaborating across onsite/offshore teams.
Comfortable in agile environments with a strong understanding of software development lifecycles and cross-functional coordination.
Capable of applying advanced statistical, AI, and cognitive techniques to extract insights and recommend actionable outcomes.