Battery Algorithms & Analytics Engineer

About Us

MEAtec is a fast-growing deep tech company developing AI-driven battery analytics, digital battery passport solutions, second-life decision-making tools, lifecycle management platforms, and edge-to-cloud BMS technologies for electric vehicles and energy storage systems. With a strong focus on sustainability and the circular economy, we collaborate with leading academics, industry partners, and international organizations to advance battery intelligence and next-generation mobility across Europe and beyond.

Position Overview

As a Battery Analytics Engineer, you will develop, implement and validate analytics for battery energy storage systems (BESS). You will turn operational data into health estimates, degradation forecasts, safety indicators and performance insights. Working with battery specialists and software engineers, you will deliver Python algorithms for integration into our battery intelligence and digital twin platforms.

Key Responsibilities

• Develop SoC, SoH and SoE estimation algorithms.
• Process BMS, EMS and PCS data and identify data quality issues.
• Calculate capacity loss, resistance trends, cycle counts, depth of discharge and cell imbalance.
• Model battery ageing and predict RUL under different operating scenarios.
• Detect anomalies, assess safety risks and identify discrepancies with BMS outputs.
• Calculate efficiency, availability and energy losses; compare performance across assets.
• Develop warranty checks, configurable thresholds and calculation settings.
• Assess planned operations and calculate their battery ageing and cost impacts.
• Implement back-testing, validate and calibrate battery algorithms using historical data; monitor accuracy, false alarms and model drift.
• Develop tested Python code and integrate analytics through REST APIs.
• Document methods, assumptions, data limitations and model versions.

Qualifications

• Bachelor’s or Master’s degree in engineering, computer science, physical sciences or a related field.
• 1–3 years of relevant experience in battery analytics, modelling, BMS algorithms or applied data science; relevant research experience will also be considered.
• Strong Python skills, including NumPy, pandas and SciPy, with experience turning analytical methods into reusable code.
• Understanding of lithium-ion battery behaviour, thermal effects, degradation mechanisms and the interpretation of voltage, current and temperature data.
• Hands-on experience with time-series analysis, parameter estimation and quantitative model validation; familiarity with statistical or machine-learning methods.
• Familiarity with Git, debugging, automated testing and technical documentation.
• Strong analytical skills, ability to work effectively in a remote team, and excellent written and spoken English at C1 level or higher.

What We Offer

• A hands-on, immersive experience in a cutting-edge R&D environment.
• Mentorship from experienced battery modeling and simulation professionals.
• Opportunity to work on real-world projects with meaningful outcomes.
• Flexible work schedule and a collaborative team culture.
• A chance to be part of a mission-driven company shaping the future of battery intelligence.