Data Scientist

Job Title: Data Scientist Company: GE Vernova Job Category: Data Science Roles & Responsibilities: The Data Scientist executes end-to-end Data Science and Machine Learning workflows under guidance to deliver measurable value in industrial operations. You will focus on data acquisition/cleaning, feature engineering, exploratory analysis, model development/validation, and contribute to deployment and monitoring in collaboration with data/platform engineering. Primary use cases include time-series forecasting, anomaly detection, and predictive maintenance, with Generative AI (GenAI) as an added advantage. Exposure to operations in Oil & Gas, Fossil Power, or Renewable Power is a plus. Job Description =================== Roles and Responsibilities * Execute DS/ML tasks across the model lifecycle: data acquisition, quality assessment/cleansing, feature engineering, and exploratory data analysis on industrial datasets (sensor/telemetry, logs, emissions, maintenance) with reproducible workflows. * Train, tune, and validate models (regression, classification, and time-series methods such as ARIMA/Prophet; anomaly detection; ensembles). Document experiments and results clearly. * Collaborate with data/platform engineering to contribute to data pipelines and model serving; support deployment activities and basic monitoring/drift checks under supervision. * Produce clean, well-structured Python/SQL code; follow coding standards, version control, and experiment tracking practices. * Create visual analyses and concise summaries to communicate findings and recommendations to teammates and stakeholders; incorporate feedback to iterate. * Assist in measuring outcomes against success metrics (e.g., reliability, availability, efficiency, emissions, cost) and maintain project artifacts (reports, annotated code). * Learn industrial context, data sources, and domain constraints; proactively identify data quality issues and propose fixes within established procedures. * Participate in POCs/pilots, including GenAI/LLM-assisted analytics workflows (analytics automation, documentation) as an added advantage. * Proficient in Python and SQL; hands-on with Pandas, NumPy, scikit-learn; basic exposure to TensorFlow/PyTorch is a plus. * Applied experience with feature engineering, model selection, cross-validation, and performance measurement for time-series and classification/regression problems. * Solid foundations in data management: ETL basics, data quality checks/cleansing, and working with large datasets. * Familiarity with cloud ML platforms (e.g., AWS SageMaker, Azure ML, GCP Vertex AI) and MLOps concepts (experiment tracking, model registry, monitoring) is a plus. * Competent in visual analytics for EDA and communicating insights; experience with dashboards or notebooks preferred. * Familiarity with big data/streaming technologies (e.g., Spark, Kafka) and real-time analytics considerations is a plus. * Exposure to industrial operations (Oil & Gas, Fossil Power, Renewable Power) is a plus; ability to learn failure modes, maintenance strategies, and process constraints and translate them into features and validation criteria. * Basic understanding of business drivers and operational KPIs (availability, MTBF/MTTR, throughput, energy yield, emissions, cost) with the ability to connect analytical results to business value. Work Location: Bengaluru, India Availability: Full time

Education Qualification: Bachelor's Degree in Computer Science or “STEM” Majors (Science, Technology, Engineering and Math) with 1-3 years of experience in Data Science/Machine Learning or closely related roles. Key Skills: Data Science, Python, SQL, Pandas, NumPy, Machine Learning, Scikit-learn Salary: INR 868500 - 960000 per yearly