Lead Data Scientist - Artificial Intelligence Models

We are seeking an experienced and visionary Lead Data Scientist to guide our data science team and spearhead our AI initiatives. As the lead, you will be responsible for setting the strategic direction for data science, mentoring a talented team, and remaining hands-on in the development and deployment of sophisticated AI models at scale.

This role is critical to our success, as you will be translating complex data from IoT devices and energy systems into actionable insights and automated solutions that help achieve a balance between people, planet and profit.

Key Responsibilities :

• Leadership & Strategy : Define and execute the data science roadmap, aligning projects with business objectives and identifying new opportunities for data-driven products.
• Team Mentorship : Guide, manage, and mentor a team of data scientists, fostering a culture of innovation, collaboration, and continuous learning.
• Model Development & Innovation : Design, build, and validate robust machine learning models for tasks such as time-series forecasting, anomaly detection, and predictive maintenance. This includes everything from data preprocessing and feature engineering to algorithm selection and hyperparameter tuning.
• MLOps & Productionization : Own the end-to-end machine learning lifecycle. Design, build, and maintain scalable, automated ML pipelines using MLOps best practices and tools.
• Technical Architecture : Collaborate with engineering and DevOps teams to select the right cloud infrastructure and tools for model training and deployment at scale.
• Cross-Functional Collaboration : Work closely with product managers, software engineers, and business stakeholders to understand requirements and deliver impactful solutions.
• Communication : Translate complex statistical concepts and model results into clear, actionable insights for both technical and non-technical audiences.

Required Qualifications :

with tools like MLFlow for experiment tracking and model management.

understanding of DevOps tools like Docker, and CI / CD pipelines using Jenkins or

GitHub Actions.

(ref : hirist.tech)