Associate II - Data Science

Role Description

Job Requirements: Working with stake holders from different business units to identify the business opportunities for leveraging the data to drive business solutions. Must have good knowledge of advanced statistical methods (automotive or manufacturing domain will be an added advantage). Mine and analyze data, applying statistical methods as necessary, discover the hidden patterns and viewing experiences to identify critical data insights. Develop customized ML/AI algorithms for the customers so that they are suited 100% to the requirements Develop reusable AI/GenAI/ML/Statistical models that can be scaled to multiple businesses with minimum customization. Translate analytic insights into concrete, actionable recommendations for business or product improvement. Data Science

Partner closely with product and engineering leaders throughout the lifecycle of project. Ensure that necessary data is captured; analytic needs are well-defined up front and coordinate the analytic needs. Independently handle the products/projects and provide technical directions to the other team members. Develop dashboards using software like PowerBI to share algorithm results to end users Strong interpersonal and communication skills: ability to tell a clear, concise, actionable story with data, to folks across various levels of the company. Technical Skills Expertise in cutting edge technologies in applied deep learning, Machine learning and AI in one or more of the following fields o Supply chain analytics: Inventory Optimization, demand forecasting, o Sales Domain : Recommendation systems, Customer Segmentation, Price Elasticity o Manufacturing analytics : Root cause analysis, scrap

reduction, cycle time reduction, warranty analytics o Computer Vision o Gen AI : RAG, Agentic RAG, Graph RAG, Chain of Thoughts, Tree of Thoughts, Content Extraction, Content summarization, Chat application, LangChain Strong expertise in Python Work experience in preparing data which includes preprocessing, feature selection, imputation, cleansing, transformation using Python Work experience in data exploration techniques, such as, mean-variance, k-means, nearest-neighbor, outlier techniques, and correlate anomalous sequences of events. Proven track record and experience with machine learning algorithms such as o Multivariate Regression, classification models, clustering algorithms, support vector machine, decision tree, random forest, neural network etc. o DOE, Forecasting, Segmentation, Uncertainty Analysis etc. Work experience in development of API, Web applications using Flask/Django will be an added advantage. Model deployment knowledge in Azure / AWS, etc. will be an advantage Deployment experience with Docker, CI & CD will be an advantage.

Skills

data science,machine learning,supply chain analytics,genai,