Senior Data Scientist

Position: Senior Data Scientist

Location: Ahmedabad (On-Site)

Experience: 8+ Years

Employment Type: Full-time

About the Role

Senior Data Scientist

end-to-end project delivery

Key Responsibilities

• Understand client business problems and translate them into

  data science problem statements

  with well-defined scope and success metrics.
• Design, develop, and deploy

  end-to-end ML pipelines

  — including data exploration, feature engineering, model training, testing, and productionization.
• Develop and implement

  predictive analytics

  ,

  statistical modeling

  , and

  optimization algorithms

  .
• Lead the development and deployment of

  Generative AI applications

  , including

  prompt engineering

  ,

  model fine-tuning

  , and

  RAG (Retrieval-Augmented Generation)

  implementations.
• Architect, design, and deliver

  AI/ML solutions

  leveraging open-source and cloud-native tools.
• Work on

  Computer Vision, NLP, and LLM-based applications

  using frameworks like

  TensorFlow, PyTorch, and Hugging Face

  .
• Collaborate with

  Data Engineering teams

  to design scalable data pipelines using platforms such as

  Databricks

  and

  Azure Data Services

  .
• Guide and mentor junior team members on technical best practices and project delivery.
• Provide

  technical consulting

  to sales and pre-sales teams for proposal building and solution demonstrations.
• Ensure solutions are built for

  performance, scalability, and operational excellence

  using MLOps and CI/CD pipelines.

Technical Qualifications (Essential)

• Education:

  B.Tech/B.E. (Computer Science, IT) / MCA / M.Sc. (Computer Science) or equivalent.

• Production Experience:

• Minimum

  2–3 ML applications deployed in production.

• Minimum

  1–2 Generative AI applications in production.

• Minimum

  3 Data Science / AI projects

  designed, developed, and deployed end-to-end.
• At least

  1 Generative AI project

  designed, developed, and delivered to production.
• Proven hands-on experience in

  Computer Vision

  and

  Core ML

  .
• Strong coding and design experience in

  Python

  ,

  PyTorch

  ,

  TensorFlow

  ,

  Spark/PySpark

  , and

  SQL

  .
• Proficiency in

  AI/ML frameworks

  and libraries such as scikit-learn, Transformers, OpenAI API, LangChain, and Hugging Face.
• Strong understanding of

  statistical modeling and predictive techniques

  , including Logistic/Multivariate Regression, SVM, Decision Trees, Clustering, Optimization, and CNNs.
• Hands-on

  prompt engineering

  and

  fine-tuning LLMs

  .
• Experience with

  REST API-based integration

  of AI/ML models.
• Working knowledge of

  DevOps, MLOps

  , and

  containerization (Docker, Kubernetes)

  for model deployment.
• Familiarity with

  cloud AI services

  (Azure AI, AWS SageMaker, GCP Vertex AI).

Primary Skills

• Python, PyTorch, TensorFlow, Spark/PySpark, SQL
• NLP Frameworks (Transformers, LangChain, RAG)
• Open Source LLMs (Llama, Mistral, Falcon, Hugging Face)
• API-based application design for AI and Data Science projects
• Experience in

  AI model fine-tuning

  ,

  RAG

  , and

  prompt engineering

• Cloud platforms (Azure, AWS, or GCP)
• Data engineering fundamentals (pipelines, data lake, data warehouse)

Secondary Skills

• Experience with

  Databricks

  and

  Azure Data Platform

  for data engineering.
• Knowledge of

  configuration management tools

  (Git, Jenkins, etc.).
• Exposure to

  container orchestration

  (Docker, Kubernetes).
• Familiarity with

  MLOps pipelines

  for automated deployment and monitoring.

Functional & Leadership Responsibilities

• Provide

  technical leadership

  across multiple AI and data science initiatives.
• Review and validate models for

  accuracy, interpretability, and business relevance

  .
• Work closely with product and domain experts to align technical outputs with strategic business objectives.
• Drive innovation by experimenting with

  emerging AI and GenAI frameworks

  .
• Mentor and upskill team members on AI/ML development and deployment practices.

Preferred Attributes

• Strong analytical and problem-solving mindset.
• Excellent communication and stakeholder management skills.
• Proven track record of delivering business impact through AI-driven insights.
• Passion for continuous learning in the evolving AI/ML ecosystem.