Job Description

Position Summary with Job Responsibilities Position Name Manager - AI_ML_Fleetedge Analytics Position level L5 DEM position name Chandrakant Patil DEM position level L4 FEM position name FEM position level Purpose of the position / Position Summary We are looking for a customer-focused & business-oriented Data Scientist who will be responsible for conducting analyses using advanced statistics and data mining techniques to enable better decision making. This role will have exposure to senior leadership teams and help Tata Motors achieve its strategic priorities. Personal Profile Education Degree in Engineering, Masters in Computer Science, Applied Mathematics, or other technical discipline Skills Experience working on Linux and Windows based infrastructure Excellent understanding of machine learning techniques and algorithms, k-NN, Naive Bayes, SVM, Decision Forests, XGBoost, PyTorch, TensorFlow, Keras etc. Strong Proficiency in programming in R, Python, PySpark Exposure to deep learning modelling Relevant Experience : Possessing 4-6 years of relevant work experience as a data scientist and solving business challenges is preferred Platforms such as Azure Cloud that provides access to databases, frameworks, programming languages, and operational tools Strong understanding of statistical analysis, predictive modelling, data engineering and feature engineering techniques Deep understanding of statistical and machine learning/deep learning to build supervised, semi-supervised and unsupervised models Ability to develop analytical approaches to answer high-level questions and develop insightful recommendations Exceptional attention to detail and ability to work effectively with minimal supervision Exposure to one or more functional areas - Sales and Marketing, Operations (Manufacturing, Supply Chain, Purchase, Quality), Finance Broad knowledge of current and emerging technology trends Job Responsibility Job Responsibility Develop and drive complex projects using advanced analytic techniques like NLP, ML, and Deep Learning etc. Preditive modelling, prescriptive analytics model through complex events processing, simulations, recommendation engines through AI, ML & advanced data visualization capabilities Excellent understanding of machine learning techniques and algorithms, k-NN, Naive Bayes, SVM, Decision Forests, XGBoost, PyTorch, TensorFlow, Keras etc. Build Statistical and machine learning/deep learning to build supervised, semi-supervised and unsupervised models Good to have exposure for Azure planform, Azure ML Studio, Databricks, Azure cognitive services etc. Experience with Data Visualization Tools like matplotlib, ggplot, d3.js., PowerBI, Tableau that help to visually encode data Using machine learning tools to select features, create and optimize classifiers Education Work Experience Enhancing data collection procedures to include all relevant information for developing analytic systems Comfortable with open-ended problems. Be able to frame your own hypothesis, create meaningful metrics, and select the modelling approach. Translate conceptual questions into data-driven analyses to allow leaders to make informed decisions Ability to extract and clean data from a variety of structured and unstructured sources and do data wrangling Monitor the results of statistical models through the use of dashboards and ad hoc analyses. Effective communication skills, both written and verbal ability to \'tell the story\' and develop executive level presentations with guidance Good applied statistics skills, such as distributions, statistical testing, regression, etc. Exposure to typical data analysis and reporting tools - Power BI, Tableau Exposure to having worked with DevOps / MLOps team will be an advantage Ability to get work done without direct reporting/ hierarchy Lead, Prepare and present analytical insights, highlight risks & mitigation actions in conjunction with business overview to leadership/ senior management teams. Proactively anticipate, analyze and develop metrics, measure the impact of analytical solutions, benchmark wherever Proactively increase value and customer satisfaction through continuous engagement, enhancement, refinements or recalibrations as needed to elevate the quality of insights, recommendation engines. Tata Motors Leadership Competencies Customer Centricity - Anticipating, understanding and focusing efforts on meeting the customer (stakeholders) needs or expectations Developing Self and Others - Recognizing continuous development is essential for success and taking steps to develop self and helping others to excel Driving Execution - Translating strategy into action and execution Leading by Example - Encouraging and following ethical standards Leading Change - Recognizing the need for change, initiating and adapting to change Motivating Self and Others - Inspiring teams and individuals Functional Competencies Tags

foundit