We are currently only accepting applications from candidates who have the right to work in the UK. We cannot sponsor.
This position is based in London and is Hybrid - 1-2 days a week in office.
Clearly gives Fleet Managers transparency over their supply chain emissions to stay compliant, identify decarbonisation initiatives, and maximise their ROI. We use AI and advanced Machine Learning to fuse data from multiple sources and provide trip-level emission and energy intensity insights.
Our ultimate vision is to be the end-to-end platform that enables the Global Transportation Industry to decarbonise supply chains and achieve operational sustainability.
With Clearly, Businesses can:
- Uncover real emissions from trip-level up to fleet-level, and identify optimal reduction initiatives, saving costs and energy
- Remain compliant and transparent to regulators and supply chain partners
- Reduce financing costs, and reduce and share risk
Clearly was recently selected as Europe’s hottest Mobility Tech Startup at The Europas Tech Startup Awards 2022. Previous winners include Spotify, Wise, Soundcloud to name a few.
About the role
As a Data Scientist with a strong foundation in Data Engineering, your role at Clearly is pivotal in revolutionising the transportation sector. You'll wield the potential of data to instigate transformative changes. You’ll work closely with our Founders, Product Manager and all Tech teams to plan, design and execute technical solutions and improvements to our product and platform.
What you’ll be doing
- Solving real business problems using statistical modelling.
- Building ETL pipelines for ingesting and processing data. This includes monitoring and enforcing data governance best practices (e.g. Privacy, Data Quality).
- Developing machine learning models.
- Writing production-ready code and deploying models. This includes complete data pipelines deployment automation (CI/CD).
- Supporting a fast-paced, iterative work environment.
- Communicating technical details and findings to a non-technical audience.
- Collaborating with cross-functional teams, including DevOps engineers, full-stack developers, and non-technical stakeholders.
What you’ll need
- 2+ years in a commercial Data Science/Data engineering role, with demonstrable experience of solving real business problems.
- BSc or MSc level education in STEM subjects.
- Strong statistical modelling background - hypotheses testing, inference, regressions, random variables.
- Strong commercial experience with Python and data visualisation, and proficient knowledge of Python, SQL, and Scala.
- Strong business and product instincts - you work iteratively and can balance academic rigour with commercial pragmatism.
- You write production-ready code and are comfortable deploying your own models.
- Ability to work collaboratively and proactively in a fast-paced environment alongside scientists, engineers and non-technical stakeholders.
- Experience communicating technical details and findings to a non-technical audience.
- A curious mind, self-starter and endlessly keen to learn and develop themselves professionally.
Nice to have
- Experience working with spatial data/big data or both.
- Experience with Data Engineering.
- Experience building ETL pipelines.
- Experience working with databricks.
- PhD degree in STEM subjects.
- Extensive Knowledge of software development life cycle processes and tools - ETL pipelines, CI/CD, MLOps, agile methodologies, version control (git), testing frameworks
- 30-minute call with Data Science Team
- Take home case study and present to the team
- 30-minute call with Data Science Team and CTO
- Final Interview with CEO
- Competitive salary.
- 28 days annual leave.
- Outstanding career progression opportunities.
- Share options.
- Flexible working arrangements - Hybrid.
- Ability to help shape our benefits package as we grow!
Right to work
We are currently only accepting applications from candidates who have the right to work in the UK.
We're an equal opportunity employer. All applicants will be considered for employment without attention to ethnicity, religion, sexual orientation, gender identity, family or parental status, national origin, veteran, neurodiversity status or disability status.