- The ideal candidate is expected to show strong business acumen and understand business problems, develop hypotheses and test the results to influence solution design.

- Have experience in understanding customer emotions and sentiments which will help you to apply and shape solutions.

- Should be hands on with various AI/ML algorithms in categories like classification, correlation, rca,prediction, anomaly deduction, etc., tools for data processing, analysis and visualization, programming languages and frameworks to derive meaningful insights. (Examples : Python, Spark, R, TensorFlow, PyTorch, AWS Kinesis, Redshift,etc).

Roles and Responsibilities :

- Develop Code using python for machine learning

- Discuss with Engineers, Product Managers to formulate hypotheses, solutions and desired outcomes.

- Act as Subject Matter Expert on ML, Data and AI statistical models and how they apply to business problems.

- You will help to implement models in Machine Learning, Optimization, Neural Networks, Artificial Intelligence (Natural Language Processing), and other quantitative approaches.

- Familiarity with Data Engineering techniques to gather, prepare, cleanse and transform data for analysis and AI automation, including data pipelines.

- Familiarity with getting data from social media - twitter, instagram, reddit, facebook, etc.

- Create prototypes, minimally viable products

- Deliver meaningful insights and predictions

- Demonstrate business value

- Mentor and coach others in the team.

Must Have Skills :

- 10+ years of hands-on working experience as Data Scientist with deep understanding of Machine Learning and AI algorithms- Linear Regression, Logic Regression, Decision Trees, K-Nearest Neighbors, Neural Networks, Random Forests, NLP/NLU, etc.

- 5+ years of experience with different frameworks such as Tensor flow, PyTorch, Keros, SparkML.

- 4+ years of hands-on coding experience with languages such as Python, R, Scala, Go, etc.

- Good experience with source control systems such as git.

Good to Have :

- Experience in prompt engineering, RAG system setup, microservices with container technologies like Docker/Kubernetes

- Working experience with using LLM and prompt engineering to solve problem,

- Handle on deploying and running services in Kubernetes

- Experience with the AWS services (Examples : SageMaker, Comprehend, Lex, Rekognition, Transcribe, EKS, Lambda, S3, etc)

- Experience with troubleshooting production systems.

- Good understanding and use of CICD systems such as Jenkins, Gitlab, etc.

Qualification :

- Bachelors degree in Computer Science Engineering, or a related technical degree.