Power Systems Distribution Specialist

About the role

You define grid analysis problems and own the modeling workflow from raw utility data to operational insights. You translate engineering constraints into scalable code while guiding decisions across teams. You act as the technical expert for utility partners in India, the US, and other markets. You will drive the analytical foundation that helps utilities understand and reduce technical losses across their distribution networks. This role requires deep engagement with real-world data complexities and the patience to methodically resolve ambiguous engineering questions. You will translate abstract regulatory and operational goals into concrete computational experiments and deliver clear narratives backed by rigorous analysis. Your work will directly influence how utilities plan investments and operate their grids in a rapidly evolving energy landscape.

Key facts

What you'll do

Build and validate distribution power flow models that compute real-time technical losses using network topology, asset parameters, and operational measurements.

Develop real-time loss computation workflows that operate continuously against live or near-live meter data to identify loss hotspots at the feeder, distribution transformer, and segment level across large networks.

Design distribution system state estimation methods that function with sparse and noisy measurement data, accommodating partial AMI coverage and inconsistent SCADA in Indian DISCOM environments.

Create automated validation pipelines that detect data quality issues, topology errors, and measurement inconsistencies, including cross-referencing GIS asset records against electrical measurements to uncover unauthorized connections and phase imbalances.

Formulate loss disaggregation methodologies that separate technical losses from commercial losses, enabling utilities to target interventions with quantified impact estimates.

Develop simulation workflows for distribution system planning, including capacity expansion studies, feeder routing optimization, and transformer sizing for greenfield and brownfield scenarios.

Conduct hosting capacity and DER interconnection studies to evaluate the impact of rooftop solar, battery storage, and EV charging on distribution feeders, analyzing voltage rise, reverse power flow, protection coordination, and thermal limits.

Perform contingency analysis and reliability studies, covering N-1 scenarios, fault current calculations, and protection coordination reviews to support utility investment planning and regulatory filings.

Model the impact of demand growth, electrification, and DER penetration on existing distribution infrastructure over five to twenty year planning horizons.

Establish voltage optimization and power factor correction studies, analyzing capacitor placement, voltage regulator settings, and conservation voltage reduction opportunities to reduce losses and defer capital upgrades.

Pioneer methods for ingesting and normalizing complex, real-world utility data at scale, including GIS shapefiles, CIM models, legacy asset registers, and heterogeneous naming conventions across utility systems.

Build automated pipelines that transform raw utility GIS and connectivity data into validated power flow models, handling missing impedance data, incomplete phasing information, and incorrect connectivity.

Develop repeatable model-building workflows that can onboard new utility client distribution networks, comprising thousands of feeders and millions of nodes, in weeks rather than months.

You will apply advanced analytical techniques to quantify the cost of losses and prioritize remediation strategies based on economic impact.

You will serve as a bridge between data science experimentation and traditional power systems engineering practice for utility stakeholders.

Key responsibilities

Operational power flow and loss analysis drive the core analytical engine of the platform, ensuring that steady-state solutions accurately reflect real-world conditions across diverse geographies.

Distribution system planning and simulation translate long-term utility needs into actionable scenarios that guide capital investment and regulatory decisions.

Data ingestion, normalization, and model construction form the foundation that enables timely, repeatable analysis across varied utility data environments.

You will work at the intersection of classical power systems engineering and modern software, translating domain expertise into scalable computational workflows.

You will collaborate directly with machine learning engineers who build demand and weather forecasting models, and with software engineers who productionize analysis into utility-facing tools.

You will be the domain authority in conversations with utility partners, understanding their operational challenges, data environments, and regulatory contexts across India, the US, and other markets.

You will mentor junior analysts by providing clear technical reviews and fostering a culture of rigorous problem solving around grid operations data.

You will contribute to the internal knowledge base by documenting methodologies, assumptions, and insights that accelerate future analysis efforts across the team.

Requirements

You must handle distribution power flow modeling and loss analysis using network topology and measurements.

You need experience with state estimation methods under partial AMI and inconsistent SCADA conditions.

You should build automated validation systems for data quality, topology, and metering anomalies in utility networks.

You have to create planning simulations for capacity, voltage regulation, and DER integration in greenfield projects.

You must analyze contingency, reliability, and power flow scenarios for long-term planning horizons.

You need to ingest and normalize complex utility data, including CIM models and legacy asset registers.

You must be comfortable working with high-dimensional numerical data and translating physical grid behavior into quantifiable metrics.

You need a strong understanding of electrical distribution principles, including three-phase power, grounding, and protection fundamentals.

Nice to have

Experience with CIM standards and utility data exchange formats.

Familiarity with electric utility operations in India and its regulatory context.

Proficiency in Python for data engineering and scientific computing.

Experience with geospatial data processing and mapping libraries relevant to asset visualization.

Understanding of conservation voltage reduction and other loss reduction techniques.

Practical notes

India, the US, and other markets may require travel; time zones will vary.

Standard work hours apply unless urgent operational analysis is needed.

Visa sponsorship details are not available for this listing.

About Pravah

Pravah is building foundational intelligence for the electric grid. We apply modern machine learning to complex physical infrastructure problems spanning grid operations, weather, and geospatial systems.