Globally, 300 million industrial electric motors power the global economy while consuming 30% of all energy produced. These motors face three critical problems: they fail unexpectedly, are often operated inefficiently and selected inadequately. This leads to high costs of unplanned downtime and massive energy waste.
At Samotics, we are passionate about solving these problems with a unique, AI-driven solution that lets industrial companies reduce downtime and cut back on their energy usage. Our unique technology is used by many of the most successful and innovative industrial companies.
We are a high-growth company (>100% revenue growth per year) with a diverse, international team working out of our brand-new office in Leiden, The Netherlands. We aim to hire only the very best talent that can scale with us as we deploy our technology across the globe.
This role is ideal for a professional with five years’ experience as a data scientist or analyst working with complex data sets. You get excited about turning data into value for customers and are enthusiastic to help grow our team’s ability to develop the algorithms and models to do so. You like collaborating with both commercial and (software) engineering teams and have relevant experience beyond consulting or advice, i.e., deploying analytical models in a scalable software product.
Samotics currently has two product teams, responsible for turning problems our customers face in optimizing for energy savings (Energy Efficiency team) and asset reliability (Asset Health team), into scalable solutions. These teams currently consist of data analysts, a product owner and subject matter experts and are led by Jeroen Röhner (Head of Energy Efficiency) and Thijs Bootsma (Head of Asset Health). As Lead Data Analyst, you’ll own the development of analytical models for both energy optimization as well as asset reliability analytics and work in close collaboration with our other technical teams, such as Software Engineering (responsible for models into our dashboard and software applications) or Data Engineering (managing integration to other systems and databases).
What you will do
As Lead Data Scientist, you are responsible for developing insights and analyses that further help solve our industrial customers’ problems. You’ll manage a team of data analysts, of which currently three are dedicated to our recently launched energy efficiency product, SAM4 Energy, and one focuses on asset reliability analytics of customers’ machinery (e.g., analyzing how overloading impacts the long-term health of assets).
You’ll focus most of your time on Samotics' energy efficiency product, defining the technical vision for our product, providing input to our development roadmap (together with the Head of Energy Efficiency) and translating business requirements to analyses and code. You manage the model development process (e.g., implementing automated testing, organizing concurrent code development) and lead new research projects (e.g., combining our own systems electrical data with rainfall forecasts and energy prices to optimize sewage network operations for energy usage and cost).
You’ll also be helping the data analysts improve their technical skillset (e.g., Python coding practices, use of Github, modular functions, etc.) as well as being a linking pin to the other technical teams (Software Engineering,, Data Engineering, etc.) to ensure the insights we develop are brought to production successfully.
Define the technical vision for analytics development as part of our product
Provide input on our product development roadmap
Own creation of analytical models from business requests and requirements
Manage technical skillset and growth of a team of 4-5 data analyst for Energy Efficiency and Asset Health (e.g., Python libraries, best code practices, etc.)
Structure, organize and align our code repository of energy savings insights with other teams in the organization (e.g., concurrent development, use of Github, etc.)
Identify improvements to our infrastructure and tooling for creating the insights
Collaborate with both customer-facing, engineering and our product teams
At least 5 years of relevant work experience
Master’s degree in engineering, data science, computer science or a related field
Experience in using Python on large data sets
Worked with complex software projects to generates analysis in a production environment (e.g., organizing multiple developers’ work through Github for a live software product)
Worked with data science and/or machine learning
Experience in bringing insights from research (e.g., in a notebook) to production (e.g., handing over to Software Engineering team for dashboard development), involving commercial teams for feedback and input
Strong at problem solving and critical thinking; able to effectively convey your viewpoint to others
Experiences/qualifications that are a plus
Affinity with energy optimization, industrial processes or equipment (e.g., drinking water production, wind turbines, pumps, to name a few examples)
Experience in using very large sets of time-series data
Entrepreneurial spirit and intrinsic motivation to solve difficult problems
What we offer:
A competitive salary
8% holiday allowance
€65 net connectivity allowance
A travel allowance
A pension plan with no contribution from the employee
Access to a wide range of learning programs
A brand-new, custom-designed office (with 90% recycled materials) at a three-minute walk from Leiden Central Station
Daily free, fresh lunches and healthy snacks when working in the office
The chance to work on cutting-edge technology that affects industry worldwide and contributes to the fight against climate change
The ability to work from home 3 days a week and from another country 1 month a year
A fun and professional company culture based on the principle of freedom and responsibility
The application procedure consists of two steps:
Introductory call by our recruiter (30 minutes)
Assessment morning or afternoon where you will speak with three of our heads of departments or team leads about your previous experience, skillset and motivation (3 hours total)