Senior Data Scientist / AI Engineer, Clearly

Open to the right fit (data science, ML, or AI expert)

Salary not provided

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Python

NumPy

Pandas

Scikit-Learn

REST API

Mid and Senior level

London

3+ days a week in office (Victoria, London)

Turning complex data into AI-powered strategic decisions

Posted today

Turning complex data into AI-powered strategic decisions

1-20 employees

B2BArtificial IntelligenceTransportBig dataMobilityAnalyticsSaaSEnvironmental

Posted today

Salary not provided

Share Options

Python

NumPy

Pandas

Scikit-Learn

REST API

Mid and Senior level

London

3+ days a week in office (Victoria, London)

1-20 employees

B2BArtificial IntelligenceTransportBig dataMobilityAnalyticsSaaSEnvironmental

Company mission

To make sense of messy data for Fleet Managers, so they can make decisions with confidence that save time, costs and emissions.

Job

Company

Role

Who you are

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science or related field (or equivalent experience)
4+ years of professional experience in data engineering, ML engineering or backend development - ideally in a startup or agile environment
Proficient in Python and familiar with libraries such as Pandas, NumPy, and Scikit-learn
Experience with database systems and data modelling
Understanding of RESTful API principles and basic asynchronous programming
Familiarity with cloud platforms (AWS, GCP, Azure) and containerisation (Docker) is advantageous
Basic knowledge of version control (Git) and CI/CD pipelines
Strong problem-solving abilities and a proactive mindset
Excellent communication skills and ability to work collaboratively in a team
Willingness to learn and adapt to new technologies and challenges
Strong analytical skills with the ability to approach challenges creatively and effectively

Desirable

Hands-on experience with LangChain, LangGraph or other LLM-agent frameworks for building and orchestrating conversational or task-driven agents
Familiarity with big-data ecosystems (Hadoop, Spark)
Experience with geospatial/spatial-data tools and workflows (PostGIS, GeoPandas)
Practical knowledge of Databricks or similar unified analytics platforms
Deep understanding of SDLC best practices, MLOps, agile methodologies and test-driven development

What the job involves

Lead the design, development and maintenance of robust data pipelines and ETL processes for seamless, scalable data flow
Architect and optimise data storage solutions (relational, NoSQL, object-store) to support diverse analytics and ML workloads
Establish and enforce best practices around data modelling, quality, lineage and governance
Design, train, deploy and monitor production-grade ML models (classification, regression, recommendation, anomaly detection, etc.)
Architect and build intelligent agents using modern frameworks to automate decision-making and workflow orchestration
Continually evaluate model performance and retraining strategies to ensure reliability and fairness
Lead the development of FastAPI-based microservices and APIs—ensuring they’re secure, observable, and capable of scaling to high throughput
Contribute to asynchronous, event-driven architectures and integrations with external systems
Mentor and coach junior members; conduct design reviews and drive code-quality standards
Partner with Product and Engineering to translate business needs into technical requirements and roadmaps
Evangelise data-driven, ML-powered solutions across the organisation
Stay at the forefront of data engineering, MLOps, agent frameworks and API development trends
Own technical debt backlogs, identify areas for refactoring, and drive automation of repetitive tasks

Application process

1. 30-minute call with Data Science Team
2. Take home case study and present to the team
3. Final Interview with our CEO

Salary benchmarks

Our take

As climate change becomes a more and more pressing issue, it is important to address the decarbonisation of road transportation, which accounts for roughly a quarter of the world's energy consumption and carbon emissions.

Clearly is a company doing just that, supplying a three-pronged approach to help businesses decarbonise their logistics and supply chains. Through the platform, users can calculate their emissions, visualising impact down to the trip level. It also analyses different strategies to determine the most effective measures to implement, and can be used to assess and reduce the cost of reaching net-zero.

The company's data-first approach has the potential to make managing emissions easier, cheaper and more accurate - an attractive proposition as businesses seek to meet evolving environmental regulations. With support from the EIT Urban Mobility accelerator program, Clearly should be well positioned to begin the next stage of its journey.

Kirsty

Company Specialist at Welcome to the Jungle

Company

Funding (1 round)

Aug 2024

$4.3m

SEED

Total funding: $4.3m

Company benefits

25 days annual leave + bank holidays
Flexible hybrid working arrangements
Private healthcare (including dental and optical cover)
Monthly wellness allowance (gym, cycle to work, etc)
Dog-friendly office
Outstanding career progression opportunities
Ability to help shape our benefits package as we grow

Company HQ

Belgravia, London, UK

Leadership

Danielle Walsh

(Founder & CEO)

Previously VP of Digital Innovation at G-20Y Association, a Board Advisor at Lyra Ventures, Governing Board Member at REEEP, and Director of TMT IB (Future Cities & New Industries) at HSBC.

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