Role Overview:
We are now recruiting talented individuals to fill our current vacancy for Principal Data Scientist to work on our projects. We are specifically seeking candidates with 10+ years of experience in Python Development and Data Science and demonstrable experience with Large Language Models (LLMs), generative AI, and AI strategy.
Qualification & Experience:
- Minimum of 10 years of experience as a Python Developer/ Data Scientist.
- Technical Responsibilities –
- Excellent proficiency in Python, with a strong focus on developing advanced skills.
- Extensive exposure to NLP, LLMs and image processing concepts.
- Practical experience with Large Language Models (fine-tuning, prompt engineering, retrieval-augmented generation), transformer architectures, and generative AI toolchains.
- Expertise in building, evaluating and deploying generative AI solutions (e.g., conversational agents, summarization, content generation, code synthesis) while applying guardrails for safety, hallucination mitigation, and ethical use.
- Proficient in version control systems like Git.
- In-depth understanding of Azure deployments, including MLOps for LLMs and model serving at scale.
- Expertise in OCR, ML model training, and transfer learning.
- Experience working with unstructured data formats such as PDFs, DOCX, and images. O
- Strong familiarity with data science best practices and the ML lifecycle.
- Tool Exposure: Advanced understanding and hands-on experience with Power BI, KNIME, Git, Azure and Python programming; familiarity with LLM platforms/APIs (e.g., OpenAI, Anthropic, Azure OpenAI, Hugging Face) and vector databases (e.g., Pinecone, FAISS, Milvus) is highly desirable.
- Data mining, cleaning and engineering: Leading the identification and merging of relevant data sources, ensuring data quality, and resolving data inconsistencies.
- Visualization: Expertise in visualizing data and modeling results using standard libraries.
- Data Analysis: Executing complex analyses against business requirements using appropriate tools and technologies.
- Software Development: Leading the development of reusable, version-controlled code under minimal supervision.
Principal Duties & Key Responsibilities:
- Leading Data Science team and grow AI integration capabilities
- Leading data extraction from multiple sources, including PDFs, images, and databases.
- Driving optical character recognition processes for digitizing data from images.
- Applying advanced natural language processing techniques to understand complex data.
- Designing, prototyping and deploying LLM and generative AI solutions that deliver measurable business value, including conversational AI, summarization, semantic search, and RAG systems.
- Implementing safe and responsible generative AI practices: prompt engineering standards, hallucination detection, bias mitigation, access control, and monitoring.
- Collaborating closely with business domain experts to identify and drive key business value drivers.
- Contributing to AI strategy by translating business goals into pragmatic AI roadmaps, helping prioritize use cases, estimating effort and ROI, and advising stakeholders on technology choices and adoption.
- Documenting model design choices, algorithm selection processes, and dependencies.
- Effectively collaborating in cross-functional teams within the CoE and across the organization.
- Proactively seeking opportunities to contribute beyond assigned tasks.
Required Competencies:
- Ability to lead team, demonstrate initiative, and provide strategic guidance.
- Exceptional communication and interpersonal skills.
- Proficiency in Microsoft Office 365 applications.
- Strong networking, communication, and people skills.
- Excellent technical writing skills.
- Effective problem-solving abilities.
- Flexibility and adaptability to work flexible hours as required.
Key competencies / Values:
- Client Focus: Tailoring skills and understanding client needs to deliver exceptional results.
- Excellence: Striving for excellence defined by clients, delivering high-quality work.
- Trust: Building and retaining trust with clients, colleagues, and partners.
- Teamwork: Collaborating effectively to achieve collective success.
- Responsibility: Taking ownership of performance and safety, ensuring accountability.
- People: Creating an inclusive environment that fosters individual growth and development.
