Associate Data Scientist Job in Sequoia Applied Technologies (sequoiaat India Pvt Ltd)

Primary Skills: 2 to 4 years experience in developing solutions leveraging AI technologies: Machine Learning, Deep Learning & NLP. A product mindset - you ask and address the most important analytical questions with a view on enhancing product impact. The candidate should be proficient in Python Experience in any visualization tool -Tableau/ Power BI/ Amazon QuickSight Experience in Machine Learning tools like Tensorflow, DeepDream etc. is a Plus Strong analytical skills, attention to detail and accuracy Expert problem-solving skills and creative thinking ability Good knowledge of General Math, Probability, Statistics, Optimization, Calculus etc. Excellent communication and presentation skills Bachelor s degree in Statistics/Science/Engineering with Mathematics as a subject from a reputed University/Institute Responsibilities: Work closely with product managers and engineering teams, understand business requirements and convert them into problem statements, develop hypothesis, design data frames, and recommend modelling approaches, measure success, testing criteria and put models in production Support the development of proofs of concepts to demonstrate the application of AI/ML capabilities in solving customer problems in collaboration with product and other development teams Prepare data for processing by organizing information, checking for any inaccuracies, and adjusting and weighting the raw data. Evaluate the statistical methods and procedures used to obtain data in order to ensure validity, applicability, efficiency, and accuracy. Identify relationships and trends in data, as well as any factors that could affect the results of model. Develop clear visualizations to convey complicated data in a straightforward fashion Bring automation to the process wherever applicable. Look to proactively identify and solve business challenges with advanced data science and analytics tools. Adhere to the principles of delivering quality deliverables by conducting regular health checks, audits, code reviews to ensure that clean and maintainable production-level code is being produced