Data Analytics and AI Manager

The ideal candidate will have a strong technical background, experience leading AI/ML and analytics teams, and the ability to align data and AI strategies with organizational objectives.

• Develop and execute AI/ML and enterprise analytics strategy, aligning with business goals to drive differentiation, operational efficiency, and growth.
• Build, mentor, and lead a diverse team of data scientists, ML engineers, analytics engineers, and AI specialists, fostering a collaborative environment that promotes innovation and knowledge sharing.
• Act as the thought leader for AI/ML and analytics technologies, staying up-to-date with industry trends, emerging platforms, and best practices.
• Drive innovation in AI methodologies, including deep learning, reinforcement learning, NLP, LLMs, and computer vision.
• Oversee the design of robust machine learning pipelines, data workflows, and analytics models, ensuring seamless ingestion, transformation, reporting, and model deployment.
• Lead the development of enterprise dashboards and analytics solutions using Power BI and Microsoft Fabric, enabling real-time insights and data-driven decision-making.
• Ensure that AI/ML and analytics solutions are scalable, efficient, and integrate seamlessly with existing systems, data infrastructure, and governance frameworks.
• Define and track KPIs for AI/ML models and analytics products, ensuring solutions deliver measurable business value and meet performance expectations.
• Monitor, maintain, and optimize deployed AI/ML models and analytics pipelines to ensure continuous accuracy, performance, and usability.
• Ensure compliance with regulatory requirements related to data governance, privacy, cybersecurity, and ethical AI.
• Collaborate with product managers, engineering, operations, and business leaders to identify opportunities, define scope, and deliver AI/ML and analytics solutions.
• Foster a culture of continuous learning, encouraging experimentation with new algorithms, tools, and reporting methodologies.
• Represent the organization in conferences, industry events, and thought‑leadership forums.

• Degree in Computer Science, Engineering, Mathematics, or a related field.
• 10+ years of experience in AI/ML, including supervised/unsupervised learning, reinforcement learning, and LLM-based solutions.
• Proven experience developing, deploying, and scaling ML models and analytics systems in production environments.
• Experience leading multidisciplinary, high-performing data and AI teams.
• Hands-on experience with Power BI, DAX, Power Query, data modeling, and enterprise reporting best practices.
• Experience with Microsoft Fabric (Data Engineering, Data Factory, Lakehouse, Warehouse, Real-Time Analytics).

• Strong expertise in ML algorithms, frameworks (TensorFlow, PyTorch, Scikit-learn), and modern data processing tools.
• Expertise in designing data models, semantic layers, and enterprise datasets for analytics consumption.
• Excellent communication skills with the ability to present complex technical concepts to both technical and non-technical audiences.
• Strong problem-solving and strategic-thinking skills with the ability to drive complex technical initiatives.
• Knowledge of ethical AI principles and data privacy regulations.
• Advanced proficiency in Python, Java, C/C++, Spark, R, Kafka, C#, MATLAB, and modern data communication formats.
• Experience with microservices, Docker, Kubernetes, and cloud platforms (AWS, Azure, GCP).
• Expertise with GraphDB, SQL/NoSQL databases, and general database architecture.
• Experience with industrial automation or power system design is a plus.
• Published research or open-source AI/ML contributions preferred.
• Familiarity with energy industry standards and documentation processes.