Data Scientist

At Intellithink, we build intelligent solutions that combine data science, advanced analytics, and domain expertise to solve complex real-world problems. Our work focuses on predictive maintenance and industrial AI, helping businesses use data to improve asset reliability, operational efficiency, and decision-making.

We are looking for a Data Scientist / Machine Learning Engineer to join our team and work on end-to-end machine learning systems, from data processing and model development to deploying scalable solutions in production.

Responsibilities

• Lead end-to-end data science projects including data processing, feature engineering, model development, deployment, and monitoring.
• Build and maintain scalable ML pipelines in Python.
• Develop time-series and signal processing solutions for industrial sensor data.
• Conduct rapid experimentation, analysis, and prototyping to generate insights.
• Collaborate with engineering teams to deploy models in production with robust APIs and monitoring.
• Build and operate ML systems using AWS services such as S3, Lambda, DynamoDB, SNS/SQS, and SageMaker.
• Work with domain experts and cross-functional teams to translate real-world problems into data-driven solutions.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electronics, Mathematics, Physics, or a related field.
• 2–3 years of experience building and deploying machine learning solutions.
• Strong proficiency in Python, with experience in NumPy, Pandas, and scikit-learn (PyTorch/TensorFlow is a plus).
• Good understanding of statistics, machine learning, and data analysis.
• Experience with time-series analysis and anomaly detection is preferred.
• Knowledge of signal processing techniques (e.g., filtering, spectral analysis, feature extraction).
• Familiarity with AWS, Docker, and MLOps practices is an advantage.
• Strong analytical thinking and ability to work in a fast-paced environment.