Experience Range - 6 to 10 Years
Location - Whitefield Bangalore
Data Scientist - Key Responsibilities :
- Design, build, and deploy machine learning models for predictive maintenance, process optimization, demand forecasting, and asset performance management.
- Work with large-scale datasets sourced from industrial systems to derive insights and inform strategic decisions.
- Develop and manage data pipelines for ingestion, transformation, and storage using tools such as Apache Spark, Airflow, or Kafka.
- Collaborate with domain experts to frame data science problems relevant to operations, manufacturing processes, logistics systems.
- Perform Exploratory data Analysis to understand data patterns and data readiness for Machine learning use cases.
- Deploy models in cloud or hybrid environments and monitor performance using MLOps best practices.
- Build and maintain visual dashboards and analytics reports using Power BI, Tableau, or Python-based frameworks.
- Communicate insights effectively to business and technical stakeholders.
- Apply generative AI and large language models (LLMs) to industrial data for document automation, decision support, and workflow optimization.
Technical Skills :
Strong proficiency in Python and ML libraries (Scikit-learn, TensorFlow, PyTorch, XGBoost, etc.).Experience in Computer vison, Image processing, NLP and multi model techniques.Experience with data wrangling and processing large datasets using SQL, Pandas, Spark, or similar.Solid understanding of machine learning, time-series forecasting, statistical modelling, and MLOps practices.Experience with LLM fine-tuning, vector databases, or industrial NLP applications.Experience deploying models on cloud platforms (AWS, Azure, or GCP) using tools such as SageMaker, Vertex AI, or Databricks.Familiarity with data from industrial systemsHands-on with visualization tools (e.g., Power BI, Tableau).Certifications : Relevant certifications in Cloud-based Architecture (AWS, Azure, or GCP) are a plus.