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Senior niche ML role reduces competition, but metro location slightly increases applicant density.
Highly domain-specific ML, optimization, and MLOps expertise required, limiting cross-industry transferability.
Explicit 11+ years and deep ML, MLOps, and generative AI requirements make shortlisting highly selective.
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Translate client business use cases into technical designs with measurable impact on solution delivery.
Review and define architecture, frameworks, and design ensuring scalability, security, and adherence to benchmarks including NFRs.
Lead solution development by selecting technologies, patterns, and frameworks to meet functional and non-functional requirements.
Total work experience of 11+ years.
Hands-on data science expertise with predictive modeling techniques like Statistical Analysis, ANOVA, Time Series, Regression, and optimization.
Strong skills in Python or R, Pandas, NumPy, Scikit-learn, with experience in GCP data science and cloud architectures (AWS, Azure, GCP).
Bachelor’s or master’s degree in computer science, Information Technology, or related field.
Experienced in deploying data science solutions with proficiency in machine learning, mathematical optimization (LP, IP, genetic algorithms, RL), and NLP.
Familiarity and hands-on experience with Generative AI technologies such as RAG, Lang Chain, Llama Index, and prompt engineering.
Capable of bridging technical and business teams, providing architectural leadership and systematic problem resolution in complex cloud environments.