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