Position : Head of Data Science (AI / ML Techno-Managerial Leader)
Experience : 13–18 years (minimum 4 years in AI / ML leadership roles)
We are seeking an experienced AI / ML leader to drive enterprise-wide data science initiatives, lead a high-performing team, and develop innovative, scalable AI / ML solutions. This techno-managerial role combines strategic thinking, hands-on expertise, and leadership to unlock business value through data.
Key Qualifications :
- 13–18 years of relevant experience in data science and AI / ML.
- At least 4 years in leadership roles within AI / ML or advanced analytics.
- Proven ability to design and deploy end-to-end AI / ML solutions using big data technologies.
- Strong background in machine learning, statistical modeling, and data mining.
- Proficient in Python, R, or similar programming languages.
- Experience with big data tools (e.g., Spark, Hadoop).
- Expertise in AI / ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Knowledge of cloud platforms (AWS, GCP, OpenShift) and MLOps pipelines.
- Experience in NLP and computer vision applications.
- Proficiency in data visualization tools (e.g., Power BI).
Key Responsibilities :
Define and execute the organization's AI / ML and data science strategy.Identify and drive high-impact AI / ML opportunities to improve decision-making and business outcomes.Lead the design, development, and deployment of advanced analytics solutions, including predictive models and recommendation systems.Apply cutting-edge techniques such as deep learning, NLP, and computer vision to solve complex business problems.Ensure scalable model development and deployment using modern MLOps practices.Build and mentor a cross-functional team of data scientists, ML engineers, and analysts.Collaborate with product, technology, and business teams to align data initiatives with organizational goals.Communicate complex analytical insights to both technical and non-technical stakeholders.Ensure high-quality, on-time delivery of data science projects.Promote best practices in data governance, model explainability, and AI adoption.Oversee the development of robust data pipelines and infrastructure to support AI initiatives.Define and monitor KPIs to measure the effectiveness and impact of AI / ML solutions.Continuously evaluate and enhance existing models to adapt to changing business needs.Skills Required
Machine Learning, Hadoop, Power Bi, Data Mining, Big Data Technologies, AI ML, Tensorflow, Nlp, MLops, Gcp, Pytorch, Computer Vision, Openshift, Spark, Statistical Modeling, Python, Aws