Staff Data Scientist

Job Responsibilities: As a Staff Data Scientist, you will be an integral member of our cross-functional team consisting of Data Scientists, Engineers, and Analysts. Your primary responsibilities will include: Collaborating closely with cross-functional teams to identify and implement data-driven solutions addressing key business challenges. Applying advanced statistical methods, machine learning and deep learning techniques to uncover trends, patterns, and anomalies in large-scale datasets. Design, develop and deploy production ready scalable solutions on edge, cloud or both (hybrid) that utilizes Signal Processing, Gen-AI, DNN, Traditional ML models or/and data-driven rules. Creating robust frameworks and tools to automate and enhance data mining, labeling, model training, and validation processes for internal ML/DL initiatives. Conducting studies, setting up automation tools and frameworks, and regularly publishing internal and external KPI audits. Develop and maintain ROI models and frameworks to quantify the business impact of data science initiatives. Analyze pre and post implementation data to measure improvements in cost efficiency, revenue generation, and overall business performance. Requirements: B. Tech, M. Tech or PhD in Data Science, Computer Science, Electrical Engineering, Operations Research, Statistics, Mathematics or a related area. Strong foundational knowledge in Statistics, Probability Theory, Machine Learning & Gen-AI. Excellent programming skills – Python(required) and C++ (desired), with strong fundamentals in object-oriented programming, algorithms, and data structures. Good understanding of database internals and schema design for relational (RDBMS) and non-relational (NoSQL) data stores. Exposure to AWS cloud services, including Kinesis, SQS, EKS, Auto Scaling Groups, etc. Knowledge of best practices in software development, including version control, testing, and continuous integration. Desired skills: Hands-on experience in handling edge deployments targeting various HW platforms. Strong foundational knowledge in signal processing Experience with ML frameworks, including Caffe, TensorRT, OpenCL, SNPE, OpenVino, and ONNX. Experience in embedded platforms, make files, build systems, and familiarity with Jenkins. Working knowledge of common industry frameworks and tools around building LLMs, such as OpenAI, GPT, BERT, etc. Experience with MLOps tools and practices for continuous deployment and monitoring of AI models.

Location: bangalore, IN

Posted Date: 6/17/2025