Data Scientist

7 days ago

Bengaluru, Karnataka, India Intellithink Industrial IoT Full time ₹ 15,00,000 - ₹ 25,00,000 per year

At
Intellithink
, we are building intelligent solutions that combine data science, advanced analytics, and domain expertise to solve complex real-world problems. Our work spans across predictive maintenance and industrial AI — helping businesses harness the power of data to improve reliability, efficiency, and decision-making.

We are now looking for a
Data Scientist / Machine Learning Engineer
to join our growing team. This is an exciting opportunity to work on end-to-end machine learning projects, from raw data processing to deploying scalable models in production. If you're passionate about turning data into actionable insights and thrive in solving challenging problems, we'd love to hear from you.

Responsibilities

  • Lead end-to-end data science projects, including data processing, KPI design, feature engineering, model development, deployment, and monitoring.
  • Design, develop, and maintain reliable and scalable ML pipelines in Python.
  • Perform rapid experimentation and build prototypes, dashboards, and analysis tools for demonstration and insights.
  • Collaborate with software engineering teams to productionize models, ensuring robust APIs, testing, observability, and documentation.
  • Leverage AWS services (e.g., Lambda, S3, DynamoDB, SNS/SQS, SageMaker) to build, deploy, and operate ML systems in production.
  • Partner with cross-functional teams and domain experts to translate business problems into measurable, data-driven solutions.
  • Research and review relevant academic papers to inform feature engineering, model selection, and product improvements.
  • Develop and implement signal processing tools for time-series data analysis and reporting.
  • Establish data and model monitoring workflows (e.g., drift detection, performance tracking), including alerting and automated retraining.

  • Maintain clear documentation of designs, experiments, and decisions for transparency and reproducibility.

  • Qualifications & Requirements

  • Bachelor's or Master's degree in Computer Science, Electronics/Communication Engineering, Mathematics, Physics, or a related technical field.

  • 2–3 years of hands-on experience delivering data-driven solutions, including deployment into production.
  • Strong proficiency in Python and core data/ML libraries (NumPy, Pandas, scikit-learn); exposure to PyTorch or TensorFlow is a plus.
  • Solid understanding of statistics, data analysis, and applied machine learning concepts.
  • Experience with unsupervised learning and time-series analysis; anomaly detection is a strong plus.
  • Strong foundation in signal processing (e.g., filtering, spectral analysis, feature extraction) with practical applications to real-world datasets.
  • Familiarity with cloud-based ML pipelines, preferably on AWS.
  • Working knowledge of containerization (Docker) and DevOps/MLOps best practices is an advantage.
  • Strong analytical mindset with a systematic, scientific approach.
  • Ability to thrive in fast-paced environments, take ownership, and learn quickly.
  • Excellent communication and collaboration skills for cross-functional teamwork.

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