Job Description: Data science Analyst

Who are we looking for?

Looking for individuals with 4+ years of experience implementing and managing Data science projects . Working knowledge of Machine and Deep learning based client projects, MVPs, and POCs. Should have expert level experience with machine learning frameworks like scikit-learn, tensorflow, keras and deeplearning architectures like RNNs and LSTM. Should have worked with cognitive services from major cloud platforms like AWS (Textract, Comprehend) or Azure cognitive services etc. and have a working knowledge of SQL and no-SQL databases and microservices. Should be adapt at Python Scripting. Experience on NLP and Text Analytics is preferred

Skillsets:

 Knowledge of Natural Language Processing(NLP)techniques and frameworks like Spacy, NLTK, etc. and good knowledge of Text Analytics

 Should have strong understanding & hands on experience with machine learning frameworks like scikit-learn, tensorflow, keras and deep learning architectures like RNNs and LSTM , BERT

 Adept at Python Scripting

 Should have worked with cognitive services from major cloud platforms like AWS and have a working knowledge of SQL and no-SQL databases.

 Should exhibit diligence and meticulousness in working with data

 Ability to Translate complex machine learning problem statements into specific deliverables and requirements

 Ability to create data and ML pipelines for more efficient and repeatable data science projects using MLOps principles

 Keep abreast with new tools, algorithms and techniques in machine learning and works to implement them in the organization

 Strong understanding of evaluation and monitoring metrics for machine learning projects

 Strong understanding of containerization using docker and Kubernetes to get the models into production

 Knowledge of distributed computing frameworks and cloud ML frameworks including AWS, Azure, and GCP

Experience

 10+ years of Software Development experience

 4+ years of experience in the Data Science and Machine Learning techniques

 Proven track record of getting ML models into production

 Hands-on experience with writing ML models with Python.

 Prior experience in ML platforms and tools such as Dataiku, DataBricks, etc. would be a plus