Data Scientist

About Client:

Mphasis applies next-generation technology to help enterprises transform businesses globally. Customer centricity is foundational to Mphasis and is reflected in the Mphasis’ Front2Back™ Transformation approach. Front2Back™ uses the exponential power of cloud and cognitive to provide hyper-personalized (C=X2C2TM=1) digital experience to clients and their end customers. Mphasis’ Service Transformation approach helps ‘shrink the core’ through the application of digital technologies across legacy environments within an enterprise, enabling businesses to stay ahead in a changing world. Mphasis’ core reference architectures and tools, speed and innovation with domain expertise and specialization are key to building strong relationships with marquee clients

Job Title : Data Scientist

Job Locations : Bangalore

Experience : 5+ Years.

Notice Period : Immediate - 15 Day..

Responsibilities:

· Experience:

· Minimum of 8 years of experience in AI development, data engineering, or related fields, with at least 5 years focused on GenAI applications.

o Proficiency in Python, with experience in libraries such as Pandas, NumPy, and PyTorch/TensorFlow.

· GenAI Expertise:

o Hands-on experience with Azure OpenAI services and non-OpenAI LLMs.

o Familiarity with LangChain, RAG applications, MCPs and prompt engineering techniques.

o The ability to navigate technology hype, identify and prioritize game-changing applications for our group and execute their development in agile squads

o A deep understanding of foundational and large language models and the vision and hands-on mindset to make your ideas come to life in ZEISS solutions

o Experience with best practices in model development and deployment (Azure Machine Learning Service/ MLflow)

o Experience with fine-tuning and deploying LLMs at scale(good to have)

· Data Engineering:

o Strong knowledge of data pipelines, and workflow orchestration tools

o Experience with connecting to enterprise systems like SAP, cloud databases, and APIs.

· Architecture & Scaling:

o Proven experience in designing and scaling AI systems for enterprise applications.

o Expertise in cloud platforms (Azure preferred) and distributed computing.

o Familiarity with containerization (Docker) and orchestration (CI/CD pipelines and terraform).

· Databases:

o Strong SQL skills and experience with relational (e.g., PostgreSQL, MySQL – good to have) and NoSQL databases (e.g., MongoDB, Cosmos DB).