Lead Data Scientist

4 days ago

Chennai, Tamil Nadu, India Sedin Technologies Full time ₹ 12,00,000 - ₹ 36,00,000 per year
Lead Data Scientist  Location: Chennai 
Experience: 10+ years    As a Lead Data Scientist at Datakulture, you will…
  • Drive end-to-end delivery of data science projects, transforming business problems into analytical solutions.  
  • Lead a team of data scientists and ML engineers, providing technical guidance, code reviews, and mentorship.  
  • Engage with clients and internal stakeholders during pre-sales to shape solution architecture, project scope, and value propositions.  
  • Collaborate cross-functionally with domain experts, product managers, and engineers to ensure solutions are practical and impactful.  
  • Stay updated on advancements in AI/ML and apply cutting-edge techniques to real-world problems.  
  • Represent Datakulture in thought leadership initiatives—whitepapers, blogs, webinars, or conference talks. 
  Qualifications  We'd love to hear from you if you...
  • Have a Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related field.  
  • Have 10+ years of hands-on experience in applied data science, statistical modeling, and machine learning.  
  • Have a track record of delivering ML projects in production, across domains such as retail, finance, or operations.  
  • Are skilled in Python, with strong knowledge of data manipulation, model development, and visualization.  
  • Are proficient in Streamlit for building interactive data apps and demos for business stakeholders. 
  • Have solid experience building and deploying APIs using FastAPI (or Flask). 
  • Understand machine learning deployment workflows and ML Ops practices (e.g., model versioning, monitoring, CI/CD).  
  • Have prior experience working with pre-sales or client-facing solutioning for analytics/AI projects.  
  • Demonstrate strong problem-solving, communication, and team leadership skills. 
  Nice to have
  • Experience publishing research papers or contributing to open-source AI/ML projects.  
  • Familiarity with modern NLP techniques, LLMs (fine-tuning, RAG, agents), and frameworks like LangChain or OpenAI APIs.  
  • Working knowledge of cloud platforms (AWS, GCP, or Azure) and scalable ML infrastructure.  
  • Exposure to BI tools (e.g., Power BI, Tableau) and data warehousing systems. 
  Our Technology Stack
  • Python and Jupyter Notebooks, SQL, Spark/PySpark 
  • Tensorflow, PyTorch 
  • Streamlit, Gradio, Flask 
  • MLflow, Weights & Biases, Docker, Airflow, FastAPI, GitHub Actions 
  • Github, Jira 
  • AWS, Azure, GCP, Dataiku, Databricks 
 

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