Joining Vantage Power (VP) will be a very special experience. Founded in 2011, VP built up a highly talented team who over the years made significant advances in the field of battery pack, control system and connectivity technologies. In 2019 the company was acquired by Allison Transmission – a global leader in propulsion technologies including hybrid and conventional powertrain products.

This acquisition has put VP into the unique position of being able to retain its entrepreneurial, dynamic and close-knit team culture while being backed by an extremely well run and profitable global business. With this comes a level of investment, resource, expertise and international reach that small businesses can only dream of, offering up immense opportunities for career development, training, travel, and the ability to see the fruits of your labour scaled to thousands of vehicles around the world.

Over the past few years the engineering team have been deploying new generation IoT devices to development vehicles, test vehicles, customer trial vehicles and others, with the intention of using this connection to evolve and improve our engineering capability.  The device hardware and cloud infrastructure are well developed but the interfaces needed to present and query the data is not.  This person will be required to evaluate technologies and test out solutions that establish data pipelines, automation, databases and other mechanisms needed to extract value from technical vehicle data and make this accessible to project teams, management and in the long run, to customers.  

Candidates must be eligible to work in the UK. Candidates already in the UK and working under Tier 2 Sponsorship will also be considered.

Responsibilities and Activities

  • As part of an R&D team, own technical and project level decisions to help generate value from vehicle Telemetry data. 
  • Engage with stakeholders (management/engineers) to map problems to analytical solutions.
  • Develop solutions, identify KPIs, track and communicate progress. 
  • Work within cost targets, trade off different approaches/tools/frameworks and deploy analysis into a production environment in the cloud or at the edge.
  • Develop new or extend existing cloud architecture to build scalable and robust solutions for automated analysis, data storage-retrieval and near realtime visualizations using Azure/Databricks services.
  • In Azure, design and deploy bespoke data dashboards for users to gain insights on problems and facilitate easy access to data using plotly, streamlit, PowerBI or other suitable frameworks.
  • Review, understand, clean and analyze data from a variety of device types and sources using python tools numpy, scipy, matplotlib and pandas.
  • Set up automated, modular and scalable data ETL and analysis pipelines/processes on Azure.
  • Using Docker containers, develop reproducible, clean analysis code with unit tests and versioning of code base (primarily python) in Github.
  • Developing models for failure detection, physical system modelling and optimization problems addressing vehicle/system performance using frameworks for modelling (scikit-learn etc.), deployment (AzureML) and experimentation (MLFlow/Databricks).
  • Use lessons learnt from R&D work as a guide to help inform the organization on how to establish an enterprise wide analytics platform.
  • Support the development of new powertrains - work with and understand mechanical and electrical systems within hybrid and electric vehicles.

Skills and Experience


  • Excellent problem-solving skills. Takes ownership of problems and sees them through to a conclusion;
  • Organized, data-driven and an analytical mind with an affinity to build and deploy solutions;
  • Strong verbal, written, mathematical and spatial reasoning skills;
  • Proficiency using Python or similar high level programming language;
  • Experience with Azure or similar cloud technology (focused around data analytics and deployments);
  • Experience with data visualization and presentation;
  • Experience with datalakes (blob storage) and/or relational, non-relational databases (azure table storage, databricks tables);
  • Proficiency in data wrangling and analytics using numpy, pandas, parquet files, matplotlib;
  • Ability to create and understand analytical models with tools like scikit-learn and ensure reproducibility with conda and Docker; 
  • Good understanding of general engineering principles related to hybrid and electric vehicle technology;
  • Motivated, enthusiastic and interested by the industry and products.


  • Automotive industry experience;
  • Experience with cloud-based data analytics tools e.g. Databricks, AzureML, Azure Synapse;
  • Experience with visualization tools e.g. Plotly Dash, PowerBI, Tableau any other;
  • Understanding of automotive powertrain (conventional/hybrid/electric) and vehicle systems (transmissions, batteries, combustion);
  • Experience building machine learning models and using advanced statistical techniques.

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