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Tier-1 brand, mid-level popular data scientist role in metro drives high competition.
ML and analytics skills are transferable, though biotech domain experience is moderately preferred.
Explicit 2–5 years requirement plus ML/MLOps skill expectations creates moderate gatekeeping.
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Develop and deploy advanced machine learning, operational research, semantic analysis, and statistical methods on large datasets to create analytics solutions addressing customer needs.
Collaborate with software developers and engineers to translate analytics algorithms into commercially viable products and services.
Conduct exploratory and targeted data analyses; manage modeling and analytics experiment pipeline leveraging MLOps; work with data engineers on data quality and cleansing.
Bachelor's or Master's degree.
2 to 5 years of professional experience in data science or related field.
Experience with analytic software/tools such as SAS, SPSS, R, or Python.
Not explicitly mentioned in the JD: Notice period or strict location requirements.
Strong foundation in machine learning algorithms and techniques with experience in applied analytics, descriptive statistics, feature extraction, predictive analytics on industrial datasets.
Proficiency in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn); experience with MLOps and cloud platforms (AWS, Azure, Google Cloud) preferred.
Experienced in working within Agile (SAFe) delivery model and collaborating with global, virtual teams.