Lead Data Scientist

What will you be responsible for? We are looking for a Data Scientist to join the DwX (Digital Workplace Experiences) team to build and enhance AI/ML solutions, with a focus on LLM fine-tuning, model evaluation, and AI-driven use cases across HR, Finance, and Enterprise workflows. This role requires a strong foundation in machine learning, data engineering basics, and Generative AI concepts, with hands-on experience in developing and improving models for real-world business problems.

• Develop, fine-tune, and optimize machine learning and LLM-based models for enterprise use cases (chatbots, automation, insights)
• Work on prompt engineering, fine-tuning techniques, and model evaluation frameworks
• Implement RAG (Retrieval-Augmented Generation) patterns using enterprise data sources
• Experiment with different models (OpenAI, open-source LLMs) to improve performance and accuracy
• Build and deploy supervised/unsupervised ML models and NLP solutions
• Perform data analysis, feature engineering, and model validation
• Apply statistical techniques to identify patterns and generate insights
• Continuously improve models based on feedback and evaluation metric

What would your day look like?

• Work closely with data engineering teams to consume clean, reliable datasets
• Understand basics of data pipelines, data modeling, and cloud platforms (Azure/Snowflake)
• Support integration of AI models into scalable data/AI platforms
• Assist in deploying models into production (batch or API-based)
• Support monitoring, performance tuning, and continuous improvement of models
• Contribute to ML/LLM lifecycle practices (experimentation → deployment → evaluation)
• Work with product, business, and engineering teams to understand requirements
• Translate business problems into data science solutions
• Present insights and model outcomes in a simple, clear manner

Who are we looking for?

• 6–9 years of experience in Data Science / Machine Learning
• Strong fundamentals in: Machine Learning (Regression, Classification, Clustering), NLP and Deep Learning basics and Statistics and data analysis
• Hands-on experience with: Python, SQL (must have) & ML frameworks (scikit-learn, PyTorch, TensorFlow)
• Exposure to: Generative AI / LLMs (GPT, Llama, etc.) & Basic fine-tuning / prompt engineering / RAG concepts
• Experience working with large datasets and data processing
• Understanding of data engineering basics (ETL, pipelines, data storage)
• Strong problem-solving and analytical skills
• Bachelor's degree in mathematics, statistics, healthcare administration, or related field.
• 5+ years of experience in Python, SQL, R, SAS