Wejo is a leader in the connected car market and is shaping the future of mobility. The connected car space is one of the fastest growing sectors in the internet of things industry. Car manufacturers are looking to extend traditional infotainment systems, insurers are seeking a better understanding of risk, users are demanding more feedback and firms are generating increasing amounts of data and require support in understanding its applications and value. We specialise in creating new services and products to help clients make the most of their data and realise its value

We bring together the brightest minds and industry experts with award-winning platform technology and advanced privacy and security to revolutionise the way we live, work and travel using connected car data, insights and analytics.

At Wejo our values drive our culture, shape our interactions and help us to achieve our goals. These values are turned into meaningful behaviours and embody our employees. We are bold, collaborative and responsible.

Role Summary

The role of the Data Scientist is to help discover and build algorithms for Wejo’s data products utilising data & analytics platforms in place for both stream and batch systems. You will be required to perform some basic engineering activities to across a wide range of datasets to prepare/curate the data.

Once the prepared data is in place, you will then utilise and apply the necessary industry/academic data models/algorithms to help understand and shape the data to underpin Wejo as a “data driven business”.

A prerequisite for everyone working in Wejo is a high level of personal resilience and the ability to manage changing priorities and complexity well.

Key Responsibilities – what I do mostly

• Provide the insights and discovery on a variety of dataset across the business

• Work with other members of the Data function to design, estimate and build big data products.

• Work with the product owners and business analysts in analysing business requirements to design and implement data structures and fine tune performance to meet those requirements.

• Review new external data sets and open data sources to understand potential usage.

• Work with Infrastructure and DevOps teams to release and maintain live products.

• Participate in establishing processes and best practices around development standards, version control, quality control, deployment, maintenance and change management.

• Ensuring a professional image of the company and themselves is presented at all times.

Other Responsibilities – what I will be doing sometimes

• Using my expertise and knowledge to help in areas of the business that need support to get the job done, whatever that might be.

Essential Skills / Knowledge & Experience – what I need to do the job

• Data Science related qualification at degree level or higher

• 2+ years of experience in the field of big data engineering.

• Strong experience with Hadoop and Spark using language of python or Scala

• Solid understanding of statistical and predictive modelling concepts, machine-learning approaches, clustering and classification techniques, and recommendation and optimization algorithms

• Knowledge of some / all of: regression, neural networks, decision trees (random forest, gradient boosted trees etc.), agglomerative clustering, k-means, gradient descent, logistic regression etc.

• Ability to analyse large, complex, multi-dimensional datasets using SQL, R and / or python

Equal Opportunity Employer: Wejo is an equal opportunity employer, committed to our diversity and inclusiveness. We consider all qualified applicants regardless of race, color, nationality, gender, gender identity or expression, sexual orientation, religion, disability or age. We strongly encourage women, people of color, members of the LGBTQIA community, people with disabilities and veterans to apply. We are actively working to be an anti-racist organization. We're committing to creating an inclusive and equitable workplace for all of our employees. You can read more about our commitment to DEI here.