Data Science Engineer

About Probus Smart Things

Probus Smart Things is pioneering next-generation communication protocols by developing sensors, edge devices, and IoT hardware that connect the physical and digital worlds. We focus on digitizing electricity distribution grids to reduce network losses and ensure electricity reaches every household efficiently. Our award-winning wireless technology and venture capital backing reflect our commitment to innovation in smart grid solutions. Our team comprises diverse technologists passionate about design, product development, and customer-centric solutions, with a culture that values ownership, agility, continuous learning, and high performance.

Role Overview

We seek an experienced Data Science Engineer skilled in building large-scale machine learning systems to lead technical initiatives impacting electricity markets and IoT product performance. This role involves turning complex, ambiguous business challenges into quantitative, algorithmic solutions and managing ML models in production environments.

Responsibilities and Expectations

• Lead and execute complex Data Science, Machine Learning, forecasting, and algorithmic decision-making projects.
• Build and deploy production-grade machine learning models for high-frequency, noisy data sets, focusing on time-series forecasting and predictive analytics.
• Translate ambiguous operational challenges into robust mathematical or algorithmic frameworks.
• Collaborate closely with founding teams in an agile startup environment to deliver impactful connected product applications used by millions.
• Utilize data-driven insights to inform decisions and validate assumptions.
• Mentor team members and foster a culture of learning and innovation.

Required Qualifications

• 7-12+ years of relevant experience in Data Science, ML, quantitative research, forecasting, optimization, or algorithmic decision systems.
• Minimum 3 years leading technical teams or complex data science initiatives.
• Proven proficiency in production deployment of ML systems including model serving, monitoring, drift detection, and automated retraining.
• Expertise in time-series forecasting techniques including multivariate, probabilistic, demand, and price forecasting using advanced modeling techniques.
• Strong background in mathematical optimization methods (e.g., linear programming, mixed-integer programming, dynamic programming, reinforcement learning).
• Advanced programming skills in Python and SQL; strong software engineering practices ensuring scalable and maintainable code.
• Experience with large data pipelines and ML infrastructure; familiarity with cloud-based ML platforms and MLOps is advantageous.
• Ability to design experiments, perform model validation, backtesting, and uncertainty estimation.
• Educational background includes a bachelor’s or master’s in Computer Science, Statistics, Mathematics, Electrical Engineering, Data Science, Operations Research, or related quantitative disciplines. Advanced degrees, especially in ML or optimization, are preferred.
• Prior experience or knowledge of Indian electricity markets (IEX, DAM, RTM, GDAM, SLDC scheduling, DSM, renewable procurement) is a plus but not mandatory.

Culture and Work Ethic

We embrace trust, clear and efficient communication, bias for rapid execution, ownership mentality, continuous learning, and a championship team culture characterized by high performance and collective success. Though the work demands intensity and frequent challenges, resting adequately to sustain long-term productivity is valued.