Data Science & Machine Learning Lead

As a Lead Data Scientist at AVEVA, your role involves driving end-to-end model development initiatives by translating business problems into scalable machine learning solutions, leading model design and validation, and ensuring measurable business impact through data-driven insights. You will be responsible for the following key responsibilities: - Lead data exploration, data quality assessment, data patterns identification, and data gap identification, coordinating with data engineering to enable reliable datasets. - Drive the complete ML lifecycle from data exploration and feature engineering to model development and validation. - Design and develop feature engineering pipelines and select appropriate ML approaches (baseline to advanced). - Build, train, and optimize models using Python, Data bricks, Azure services, or other tools. - Develop classification, regression, clustering, and forecasting models using appropriate algorithms and tuning techniques. - Select appropriate algorithms based on problem context. - Establish robust evaluation: validation strategy, metrics, error analysis, bias checks, and model explainability. - Identify new AI opportunities, contribute to roadmap planning, and promote data-driven decision-making. Desired skills for this role include: - 8-12+ years of experience in Data Science/Machine Learning. - Strong expertise in Python. - Experience with deep learning frameworks preferred. - Strong foundation in statistics, probability, and mathematics. - Exposure to cloud platforms (AWS, Azure, GCP) is desirable. - Ability to interpret complex data and communicate insights clearly. - Experience with supervised learning (classification/regression) and unsupervised learning (clustering). - Time series/NLP/deep learning (as relevant to the role). - Experience with tools like Data Bricks or similar is desirable. - Experience in industries like Oil & Gas, Utilities, Water, Data Center, or CPG. - Experience in developing forecasting, prediction, prescription, or anomaly detection models for the above industries. - Strong communication skills: translate security risk into engineering actions and business impact. - Ability to drive adoption without 'blocking' delivery - pragmatic and risk-based. - Leadership, mentoring, and cross-functional influence. In addition, AVEVA is a global leader in industrial software with a dynamic global team of 700+ engineers, developers, consultants, solution architects, and project managers. The company is committed to embedding sustainability and inclusion into its operations, culture, and core business strategy. If you are analytical, pragmatic, and driven to make a tangible impact on the sustainability of the industrial sector, AVEVA offers a rewarding work environment where you can empower customers to harness the full transformative potential of its solutions. To apply for this position, submit your cover letter and CV through the AVEVA application portal. AVEVA is committed to recruiting and retaining people with disabilities and provides reasonable support during the application process as needed. Find out more about AVEVA's benefits and hiring process at aveva.com/en/about/careers/. As a Lead Data Scientist at AVEVA, your role involves driving end-to-end model development initiatives by translating business problems into scalable machine learning solutions, leading model design and validation, and ensuring measurable business impact through data-driven insights. You will be responsible for the following key responsibilities: - Lead data exploration, data quality assessment, data patterns identification, and data gap identification, coordinating with data engineering to enable reliable datasets. - Drive the complete ML lifecycle from data exploration and feature engineering to model development and validation. - Design and develop feature engineering pipelines and select appropriate ML approaches (baseline to advanced). - Build, train, and optimize models using Python, Data bricks, Azure services, or other tools. - Develop classification, regression, clustering, and forecasting models using appropriate algorithms and tuning techniques. - Select appropriate algorithms based on problem context. - Establish robust evaluation: validation strategy, metrics, error analysis, bias checks, and model explainability. - Identify new AI opportunities, contribute to roadmap planning, and promote data-driven decision-making. Desired skills for this role include: - 8-12+ years of experience in Data Science/Machine Learning. - Strong expertise in Python. - Experience with deep learning frameworks preferred. - Strong foundation in statistics, probability, and mathematics. - Exposure to cloud platforms (AWS, Azure, GCP) is desirable. - Ability to interpret complex data and communicate insights clearly. - Experience with supervised learning (classification/regression) and unsupervised learning (clustering). - Time series/NLP/deep learning (as relevant to the role).