Full Stack Data Scientist

Job Description

Role Senior/Junior Data Scientist /Senior Software Engineer Educational Qualification:- Bachelor of Technology in Computer Science or related field Years of Experience : 4-10 Years Location:- Bangalore or Kochi ( Both location Work From Office) # of Positions Multiple (includes Junior and Senior Data Scientist Positions) Required Skills: Senior Data Scientist - Out of 7+ total years of Experience, 5+ years of experience as a full-time data scientist, machine learning researcher, or machine learning engineer Junior Data Scientist - Out of 4+ total years of Experience, 2+ years of experience as a full-time data scientist, machine learning researcher, or machine learning engineer Fluency in R, Python, and experience with common data science libraries, such as Pandas, numpy, and scikit-learn Experience using neural networks and/or Deep Learning techniques and relevant Python platforms/APIs such as Tensorflow, PyTorch, and Keras in a production setting Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks Experience with NLP (especially sentiment analysis, entity recognition, and use of the SpaCy library) Experience with SQL databases and SQL queries Self-starting, with the interest and passion to contribute in a fast-paced start-up like environment Experience working on or with cloud platforms (AWS, GCP, Azure) Very Good understanding of DevOps Roles and Responsibilities Build, deploy, monitor, and manage Machine Learning models Identify valuable input features and implement a means for calculating them (feature engineering) Investigate, clean, analyze, and otherwise prepare new data sources for use in higher-order analysis or as input into model features Data analysis and presentation using data visualization techniques, sometimes to broader audiences within or outside of Terawe Transition models from research to production, working with Data Engineers Fine-tune model performance in a production setting using adaptive/incremental machine learning techniques Map customer and/or product requirements to correct modeling, analysis, and/or visualization approaches Recommend ways to improve data reliability and quality and implement them Collaborate with Product development team to plan new features