Senior Data Scientist - Gen AI

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Key Responsibilities:

• Architect and implement scalable AI/ML solutions, including robust MLOps pipelines for CI/CD, model monitoring, and governance.
• Lead the development of Generative AI and NLP applications such as text summarization, conversational AI, and entity recognition.
• Design and optimize large-scale data pipelines using PySpark and SQL.
• Drive scalable ML model development, deployment, and performance tuning.
• Collaborate with cross-functional teams to align AI efforts with strategic business goals.
• Mentor and guide junior team members on best practices and technical direction.

Required Qualifications:

• Bachelor’s degree with 10–12 years of experience in Data, AI, and Machine Learning domains.
• Proficient in Python (Pandas, NumPy, PyTorch, TensorFlow) and SQL.
• Hands-on experience with MLOps tools like MLflow, Kubeflow, Docker, Kubernetes, and CI/CD pipelines.
• Deep understanding of Generative AI and NLP technologies, including transformer models (e.g., GPT, BERT), Hugging Face, and LangChain.
• Strong background in data engineering using PySpark and distributed data processing.
• Experience with one or more major cloud platforms (AWS, Azure, or GCP) is a plus.

Mandatory Skills:

• Expertise in data architecture, data modeling (dimensional, relational), and hybrid cloud/on-prem environments.
• Strong proficiency in Python and PySpark; advanced SQL skills.
• Familiarity with entity resolution and data governance tools.
• Exposure to Generative AI, Machine Learning, or LLM integration.
• Preferred experience with financial products, general ledger (GL) data, or finance operations.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Other

• Industries

  IT Services and IT Consulting

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