Senior Data Scientist
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Protocol Intelligence
Data-driven signals on your job's competitivenessTier‑1 brand, mid‑level ML role with broad AI/NLP demand and metro hiring increases competition.
Core ML/NLP skills are transferable, but preferred financial domain experience raises sensitivity to medium.
Explicit 6–8 year requirement plus mandatory ML/LLM, cloud, and production skills yields high strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Own the product vision and delivery of a data management framework encompassing data acquisition, cleaning, transformation, and analytics workflows for financial data.
Support end-to-end AI/ML lifecycle including design, experimentation, deployment, and continuous improvement aligned with financial analytics needs.
Collaborate with operations, engineering, and analytics experts to translate business data needs into integrated platforms and maintain forward-looking strategies through market trend awareness.
Minimum Requirements
6-8 years of experience in data science, analytics, or statistical modelling roles.
Master’s degree in Statistics, Mathematics, Computer Science, or Engineering specializing in Data Science/AI, with proficiency in Python, R, and SQL.
Strong expertise in NLP, deep learning, LLMs, RAG workflows, Python, and core ML/DL libraries (TensorFlow, PyTorch, Scikit-learn).
Experience deploying AI solutions on cloud platforms (AWS and/or Azure) and use of Git-based version control and CI/CD pipelines.
Ideal Candidate Profile
Experienced in designing financial analytics data solutions with a strong focus on AI/ML model development, tuning, and production deployment.
Capable of leading technical execution collaboratively with engineering, project delivery, and analytics domain experts in a distributed, global, or financial services environment.
Skilled at communicating complex technical concepts clearly to diverse stakeholders including senior management and executives.