Lead Data Scientist

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 systems

Hands-on with visualization tools (e.g., Power BI, Tableau).

Certifications : Relevant certifications in Cloud-based Architecture (AWS, Azure, or GCP) are a plus.