Data Scientist

Role and Responsibility

• We are seeking for a Data Scientist.
• Groom AI/ML Use Cases:
  Collaborate with our manufacturing and business teams to pinpoint opportunities where AI and machine learning can solve problems, improve efficiency, and create value.
• You’ll help define project scopes and success metrics.
• Execute End-to-End ML Projects:
  Take ownership of machine learning initiatives from start to finish.
• This includes everything from data collection and preparation to model development, deployment, and ongoing monitoring in production environments.
• Programming & Data Engineering:
  Write clean, efficient code (primarily in Python) to build data pipelines, develop machine learning models, and automate analytical workflows. You’ll also work with SQL for data extraction and manipulation.

• Dive deep into manufacturing data (from sources like MES, ERP, and IoT sensors) to uncover patterns, engineer features, and build robust predictive or prescriptive models (e.g., for quality, maintenance, or process optimization).

• Translate complex technical findings into clear, understandable recommendations for non-technical stakeholders, helping them make data-driven decisions.

• 3+ years of experience in AI, Machine Learning, or Data Science, with a strong preference for experience in a manufacturing or industrial setting.
• Technical Prowess:
  Proficiency in Python and its key ML libraries (e.g., scikit-learn, Tensor Flow, PyTorch).
• Strong SQL skills for data querying and manipulation.
• Familiarity with data visualization tools (e.g., Power BI, Tableau).
• Basic understanding of MLOps concepts for model deployment and management.
• Domain Knowledge (Nice to have):
  Understanding of manufacturing processes, data sources (like MES, ERP), and common challenges (e.g., quality control, predictive maintenance, order backlog etc).
• Problem-Solving
  
  Skills:
  
  A curious mind and the ability to break down complex problems into manageable, data-driven solutions.

• Manufacturing Domain exposure.
• Experience with cloud platforms (AWS, Azure, Google Cloud Platform).
• Knowledge of time-series analysis, anomaly detection, or optimization techniques.

• Excellent communication skills to work effectively with diverse teams, from plant operators to senior leadership.