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Data ML Engineer

Are you a Data ML Engineer who is comfortable with working closely with business stakeholders and other data profiles for building features into our 'feature store'? Then start bringing a zero-carbon world closer every day by joining us as our Data ML Engineer!

 

Are you a Data ML Engineer who is comfortable with working closely with business stakeholders and other data profiles like Data modelers and Data strategists for providing meaningful insights to the business through Dashboards, Reports, Ad hoc analysis and other means necessary? Do you get energized by identifying and building data features into the 'feature store'? Then you might be interested in joining BDR Thermea Group as our Data ML Engineer and start contributing towards bringing a zero-carbon world closer every day!

This is what we see as your role

The business development unit Digital and Controls is responsible for the development of advanced controls and system management solutions for the BDR climate products including heat pumps, gas heated & electrical boilers, solar solutions, and cooling solutions. In modern climate solutions digitalization, connectivity, IoT and data are a crucial element to achieve ambitious objectives in developing customer focused comfort climate solutions which also reduce energy consumption and carbon footprint.

As part of this ambition we believe in the need of a professional data and analytics team who will fuel our data infrastructure and explore the power of data in supporting the energy transition by providing data driven connected services to our customers. Therefore we are setting up a team with data scientists, data modelers, data & ML engineers and data analysts

As a Machine Learning Engineer, You will be working with Data scientist and Data modeler to identify and build data features into the ‘feature store’. You are familiar with the feature engineering techniques.

In addition, your Data Engineering and Devops skills together with the basic understanding of Machine Learning capabilities will help you to deploy and maintain Machine Learning / Data Science systems in production reliably and efficiently.

You will be engaged with the different stakeholders (IT operations, Infrastructure) to work for defining and bringing maturity to the ML operational (ML Ops) processes.

You will work in close collaboration with our Data Scientists, and ensure the maintenance and further evolution of our Data Science assets.

Your knowledge, skills, experience and character include

  • More concretely, your responsibilities will encompass following activities:

  • Industrialization of ML models developed by Data Scientists.
  • Development of framework for uniform industrialization of all models
  • Ensuring our model lifecycle management activities
  • Model monitoring – check availability & validity of scores, intake of new models, design framework for scores & evaluation, report on model lift and model performance
  • Co-creation, documentation and maintenance of a ML framework that allow users to quickly train models by automating many steps (in collaboration with Data Scientists)
  • Improve standard (mature & industrialized) Data Science models following the model framework (in collaboration with Data Scientists)
  • Run and maintain our analytical and model base tables
  • Monitor the activities on our Data Science platform: disk/capacity usage, follow-up on downtime issues, serve as SPOC
  • Coach DaC Data Scientists on their programming/coding skills and approach

Skills

  • Experience with leading ML platforms such as Azure Machine Learning, AWS SageMaker,
  • Familiar with major machine learning frameworks such as scikit-learn or PyTorch for building machine learning models
  • Good level of knowledge and expertise in using several programming languages (Python, PySpark, SQL) and libraries commonly used in scientific computing and machine learning.
  • Proven experience in the automation of data pipelines, and knowledge of feature stores and cloud data warehouses. 
  • Knowledge in Dockers, Kubernetes is a plus
  • Knowledge in Azure Synapse is a plus
  • Hands-on experience with software development best practices, particularly in a collaborative, hybrid environment.
  • Hands-on experience with object-oriented programming.
  • Experience in Power BI or Qlik or other data visualization tools.
  • Good understanding of statistics and statistical concepts
  • Proven stakeholder management skills

Attitude

  • You have a problem solver mindset
  • You have excellent communication & interpersonal skills
  • You like to focus on innovation
  • You are organized and structured
  • You have Foresight Thinking
  • You are Proactive, independent and responsible
  • You have mindset to cooperate with Data Scientist

What’s it like to work at BDR Thermea Group?

You will work in a motivated, technical organization with a high level of ambition. You’ll receive an attractive remuneration package, flexible working hours, and many opportunities to remain up-to-date with the latest sector developments through training and courses. In addition to this, we also offer you:

  • An international career in a challenging environment
  • Passionate and professional colleagues who love what they do
  • Working closely along our Strategic Initiatives contributing towards the energy transition
  • Being part of BDR Thermea Group and contributing to this

Are you ready to dedicate your career to winning the energy transition?

Apply by clicking the button below and submitting your CV and motivation.

About BDR Thermea Group

We are a leading manufacturer and distributor of sustainable climate and sanitary hot water solutions and services around the world. We provide smart thermal comfort solutions for residential and commercial buildings with near-zero carbon footprint. With over 6,700 employees across Europe, North America, Turkey, Russia and China and annual sales close to €1.8 billion, we operate in over 102 countries worldwide. We own and sell many of the leading brands for heating products, including Baxi, De Dietrich, Remeha and Chappee.