enakronIC

Role Description We’re seeking a Prescriptive Analytics Modeller with strong knowledge of mathematical optimization, energy systems, and algorithmic decision-making to develop optimization models for the optimal scheduling and operation of Battery Energy Storage Systems in electricity markets. The role focuses on designing, implementing, and validating algorithms that support energy market participation, flexibility trading, arbitrage, peak shaving, ancillary services, and grid-aware dispatch. The ideal candidate combines solid optimization skills with an understanding of power systems, energy markets, and practical software implementation. This position sits at the intersection of energy analytics, operations research, AI-driven decision support, and industrial software development, contributing to enakronIC’s solutions for intelligent energy management and edge-enabled optimization. Key Responsibilities - Design and implement optimization models for the scheduling and dispatch of Battery Energy Storage Systems in day-ahead, intraday, balancing, and flexibility markets. - Develop mathematical programming formulations for energy arbitrage, peak shaving, self-consumption maximization, demand response, ancillary services, and multi-objective BESS operation. - Translate business and operational requirements into prescriptive analytics workflows, including objective functions, constraints, technical limits, and market rules. - Implement optimization algorithms using tools such as Python, Pyomo, CVXPY, Gurobi, CPLEX, OR-Tools, or equivalent frameworks. - Collaborate with power systems engineers, AI/ML engineers, and software developers to integrate optimization modules into energy management platforms and edge-residing infrastructures. - Analyze time-series data, forecasts, market prices, asset constraints, and grid signals to support robust and data-driven scheduling decisions. - Validate optimization outputs through simulations, scenario analysis, sensitivity analysis, and performance benchmarking. - Contribute to the development of scalable prescriptive analytics pipelines for real-world energy assets, including BESS, PV, flexible loads, EV chargers, and microgrids. Qualifications - 2–5 years of experience in optimization, operations research, energy analytics, power systems, or a related technical role. - Strong knowledge of mathematical optimization, including linear programming, mixed-integer linear programming, convex optimization, and multi-objective optimization. - Hands-on experience with Python and optimization libraries such as Pyomo, CVXPY, PuLP, OR-Tools, Gurobi, CPLEX, or similar. - Familiarity with electricity markets, BESS operation, renewable energy integration, demand response, or energy management systems. - Ability to formulate real-world scheduling problems into mathematical models with clear objectives, constraints, and operational assumptions. - Experience with time-series data, forecasting outputs, market price signals, and scenario-based analysis. - Understanding of battery technical constraints, such as state of charge, charge/discharge limits, round-trip efficiency, degradation, cycling limits, and reserve capacity. - Experience working in fast-paced R&D, AI/ML, energy, or industrial software environments is a strong plus. - Passion for building practical optimization tools that transform complex energy problems into actionable operational decisions. Benefits - Opportunity to work on cutting-edge AI and optimization technologies shaping the future of Industry 5.0, smart energy systems, and intelligent edge infrastructures. - A collaborative, research-driven, and international environment at the intersection of AI, power systems, optimization, and industrial innovation. - Hands-on involvement in real-world energy management pipelines, including BESS scheduling, market participation, flexibility services, and edge-enabled decision support. - Continuous learning opportunities, including mentorship, applied R&D, and exposure to energy markets, prescriptive analytics, and edge AI architectures. - Competitive compensation package based on your experience and performance. - 25 days of paid annual leave to recharge and enjoy life outside of work. - Private health insurance and access to wellness benefits, including team yoga sessions.