& Summary:Data Scientist

Responsibilities:

• Proficient in programming languages like R, Python, and database query languages like SQL, Hive, Pig is desirable. Familiarity with Scala, Java, or C++ is an added advantage.

• Proficient in Statistical modelling and Machine techniques such as time series forecasting, Reliability models, Markov Models, Stochastic models, Bayesian Modelling, Classification Models, Cluster Analysis, Neural Network, etc.

• Good exposure to deep learning and associated frameworks (PyTorch, TensorFlow, and Keras).

• Ability to perform preprocessing of structured and unstructured data: Processing, cleansing, and validating the integrity of data to be used for analysis.

• Strong working experience with cloud platforms: build, train, and deploy ML Models on Azure/AWS/GCP.

• Good working knowledge in distributed computing environments / big data platforms (Hadoop, Elasticsearch, etc.) as well as common database systems and value stores (SQL, Hive, HBase, etc.).

• Hand-on experience in the MLOps (Dockerization, REST APIs and the CI/CD/CT processes).

• Adaptation of foundation models/LLMs to address specific business challenges.

• Utilizing version control for maintaining codebase integrity and collaboration, fostering a collaborative and error-free development environment.

• Design, deploy and manage prompt-based models on LLMs for various NLP tasks.

• Build and maintain data pipelines and data processing workflows for prompt engineering on LLMs utilizing cloud services for scalability and efficiency.

• Familiarity with LLM orchestration and agentic AI libraries.

• Good understanding of business and ability to translate domain problems to data science problem.

• Ability to communicate effectively with both technical and non-technical stakeholders.

Mandatory skill sets:

• Python, GenAI,Machine learning,data science

Preferred skill sets:

• Dataanalysis, SQL, MLOPS

Years of experience required:

1-7 years

Education qualification:

BE/B.Tech/MBAMCA