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
