Data Science & AI Capability Manager

Spearheads the development and implementation of data-driven strategies to optimize manufacturing processes, product quality, supply chain, customer insights, and overall business performance. This role involves leading a team of data scientists and analysts in applying machine learning, statistical modeling, and advanced analytics to large and complex datasets. The ideal candidate combines technical expertise with strong business acumen to transform data into actionable insights that drive innovation and efficiency across the organization.

Key Responsibilities
Lead the end-to-end development of data science projects, from business understanding and data exploration to model deployment and monitoring.

Design and implement predictive models and machine learning algorithms to solve business problems (e.g., demand forecasting, quality prediction, preventive maintenance).

Collaborate closely with cross-functional teams including IT, Engineering, Production, and Sales to identify opportunities for data science application.

Mentor and manage a team of data scientists and analysts, ensuring high-quality project delivery and capability building.

Establish best practices for data science workflows, experimentation, version control, and model evaluation.

Communicate technical findings clearly to stakeholders through data storytelling, visualizations, and presentations.

Drive the adoption of AI and machine learning tools across departments, supporting digital transformation initiatives.

Stay current with industry trends and emerging technologies to guide the team and influence the organization’s data strategy.

Qualifications
Education:

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Engineering, Applied Mathematics, or a related field.

PhD is an advantage.

Experience:

At least 5–7 years of hands-on experience in data science, with a minimum of 2 years in a leadership or mentoring capacity.

Experience in a manufacturing, industrial, or supply chain-focused environment is highly preferred.

Technical Skills:

Proficient in Python and/or R for data analysis and model development.

Strong command of SQL and working knowledge of data engineering concepts.

Experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, XGBoost).

Familiarity with cloud platforms and tools (AWS, Azure, GCP, Snowflake, Databricks).

Proficient in data visualization tools like Power BI, Tableau, or Matplotlib/Seaborn.

Other Skills:

Strong leadership, project management, and communication skills.

Ability to translate complex technical solutions into actionable business insights.

Strategic thinking and problem-solving mindset.

Certifications (preferred):

Certified Data Scientist or Machine Learning certification (e.g., AWS Certified Machine Learning, Microsoft Certified: Azure Data Scientist Associate).

Agile or project management certifications are a plus.

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