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Vaibhav GhildiyalVG

Vaibhav Ghildiyal

Energy Analytics & ML Consultant

150 €/jour
Munich, DE
8-15 ans

Délai de réponse moyen : 1h

À propos de Vaibhav

I build products and strategies where energy and technology meet. Over the last 10 years, I’ve worked across power & energy markets, energy storage, data centers and EV charging, but what truly excites me is how AI and data-driven tools can reshape the way we design, operate, and trade energy systems.

Whether it’s developing market strategies, leading product teams, or optimizing battery performance with machine learning, my focus has always been on turning complex challenges into usable, real-world solutions. I enjoy working at the intersection of energy infrastructure, software, and data science, aligning technology with the realities of the energy sector.

I’m passionate about building products that aren’t just technically sound but genuinely solve problems.
  • Anglais

    Bilingue ou natif

  • Hindi

    Bilingue ou natif

  • Allemand

    Capacité professionnelle limitée

En télétravail uniquement
Travaille majoritairement à distance

Expériences

  • Gridmetry GmbH
    Head of Energy Markets
    ENERGIE
    janvier 2025 - juillet 2025 (6 mois)
    Munich, Germany
    • ◦ Led market entry for Nordic ancillary services, enabling successful participation in FFR, FCR, aFRR, and mFRR for large flexible assets including Bitcoin miners and data centers >50 MW
    • ◦ Structured and executed renewable energy investment strategies, delivering >€1M in client savings through a strategic solar project in Sweden
    • ◦ Built and managed a cross-functional team of 4 engineers to develop an in-house SaaS platform, improving energy bidding optimization and decision-making via a centralized analytics dashboard
    • ◦ Secured critical grid infrastructure by negotiating procurement of a 30 MW distribution transformer, reducing delivery risk and optimizing capex for a major energy project
    Market analysis Data science Data analysis Machine learning Deep Learning
  • Numbat GmbH
    Energy Market Analyst
    avril 2023 - janvier 2025 (1 an et 9 mois)
    Munich, Germany
    • ◦ Led development of quarterly Market and Product Intelligence reports, analyzing EV charging (AC, DC, HPC) pricing trends, competitor positioning, and regulatory developments to improve forecasting accuracy and strategic alignment across product and business teams
    • ◦ Designed and implemented a multi-layer simulation tool enabling location partners to optimize peak shaving and solar PV utilization, reducing energy procurement costs through spot-market-aligned charging strategies
    • ◦ Streamlined cross-team analytics by integrating IoT product data from ThingsBoard into Tableau dashboards via Swagger-based APIs, improving real-time visibility for Energy Services and Business Intelligence stakeholders
    • ◦ Conducted comprehensive financial analyses of dynamic pricing models, evaluating solar PV and spot market scenarios to inform product strategy and commercial decision-making
    • ◦ Assessed EV charging infrastructure requirements across customer demand profiles, site selection constraints, and AC/DC deployment trade-offs, directly influencing roadmap priorities and rollout models
  • Unicorn Energy AG
    Energy Analyst
    septembre 2021 - janvier 2023 (1 an et 4 mois)
    • ◦ Developed automated testing and validation frameworks for smart battery and fuel cell systems, improving reliability and scalability of energy storage deployments
    • ◦ Applied LSTM-based time-series models to estimate State of Charge (SOC) and State of Health (SOH), enhancing predictive maintenance accuracy and lifecycle forecasting for battery and fuel cell assets
    • ◦ Supported operation and maintenance of residential energy storage systems by managing monitoring dashboards, analyzing performance anomalies, and coordinating customer support workflows to improve system uptime
    • ◦ Built data acquisition and monitoring pipelines using Linux and Python to analyze system performance trends and inform improvements to techno-economic models for battery usage optimization

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Formations

  • M.Sc. Energy Engineering
    Technical University Berlin
    2019

Compétences (14)

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