Senior Data Scientist, Pricing - Remote Working (UK)

Remote - London, England, United Kingdom

Applications have closed

We are Zego - a commercial motor insurance provider that powers opportunities for businesses, from entire fleets of vehicles to self-employed drivers and riders. We combine best-in-class technology with sophisticated data sources to offer insurance products that save businesses time and money.

Since our inception, we have believed that the problem with traditional insurance is that it holds businesses back. It’s too expensive and time consuming, and it no longer suits businesses who use vehicles to earn money. Our products represent a solution to this problem for businesses based across the UK, Europe and beyond.

So far, we have raised over $200 million in funding and we were the first UK insurtech to be valued at over $1 billion. We were also the first to be awarded our own insurance license and recently won Tech Company of the Year 2020.

At Zego, we are proud to say we have a diverse and inclusive team, unified by our shared values and mission. Our people are the most important part of our story and everybody at Zego, no matter their role, has an integral part to play.

Overview of the Data Science team:

The mission of the Data Science team at Zego is to leverage novel data sources and modern computational tools to deliver value through data-driven insights, personalised pricing and insurance product innovation. It is a growing team, responsible for all the aspects related to data, including data sourcing, cleaning, extraction, problem formulation, implementing and testing models, productionising new exciting tools and algorithms and designing scalable tools, practices, and systems to support data science analysis and deployment. The team partners closely with Product, Pricing, Engineering and wider Commercial and Business functions to find the best ways to incorporate statistical models and evidence-based decision making into Zego’s products and processes.

Purpose of the role:

The Data Science team is looking for an experienced Data Scientist to lead Zego’s efforts in pricing. The focus will be on the development of new insurance pricing models, leveraging novel sources of behavioural data and state-of-the-art machine learning techniques. This is a dynamic role where you will work closely with Data Scientists, Engineers and Actuaries to improve Zego’s risk identification and selection capabilities. You will have a central role in researching, testing and deploying new pricing models and powering Zego’s pricing strategies through data-driven insights and evidence-based decision-making.

Sitting at the heart of Zego’s industry leading data team, you will have the full support of Zego’s exceptional engineering, data and pricing teams to build data pipelines, develop models and build tooling for feature engineering, model training, deployment, impact assessment, price simulation, and performance monitoring. You will work on projects involving data acquisition, signal processing, behavioural modelling, actuarial risk assessment, productionalisation and post-deployment analytics, giving you a wide range of exposure and plenty of chances to develop as a data professional and opportunities to move into more senior positions in the organisation.

The role is suited to a candidate with ample data science experience, ideally in the areas of signal processing, insurance modelling, predictive analytics, pricing and risk management. You will have proven skills using a programming language such as Python (or R), skill with SQL, and an understanding of good development practices (git, code review, documentation). You will be given the support and backing you need to develop your skills, including on the job training, L&D budget, and a personal career development plan.

About the role:

  • You will dive into the heart of Zego R&D efforts and help to build market leading risk identification and selection capabilities.
  • You will work with various types and diverse datasets, including claims, driver behaviour, shift and trip information, traffic, weather, telemetry, geospatial data, web and smartphone sensors.
  • You will work closely with the ML Engineering team to design, develop, deploy and maintain industry leading pricing models and technology.
  • You will contribute to improving Zego’s understanding how driver behavior relates to actuarial risk and how Zego’s can leverage the insights to disrupt the way the industry currently operates.
  • Your models will have an outsized impact in optimizing the balance between profitability, risk, and growth.
  • You will define and improve rigorous reproducible research practices to maintain excellence in all you do.
  • You will become a data subject-matter-expert in the evaluation and development of new pricing systems tools and their implementation.
  • You will conduct pre- and post-deployment impact analysis to quantify the success of new strategies and implementations.
  • You will assist stakeholders to articulate their pricing strategy requirements, guiding and challenging where appropriate.
  • You will proactively identify opportunities for using ML, work on uncertainties, and drive projects end to end independently with a focus on results
  • You will help to standardize and automate the analytics pipeline for use across the pricing organisation.
  • You will communicate data-led recommendations to senior stakeholders, both written and orally.
  • You will champion a data-driven approach as you partner with stakeholders of different seniority showcasing your inclination as an outstanding individual contributor and develop into other senior roles.
  • You will use modern tools and methods and techniques to promote automation in Zego’s analytics operations.
  • You will constantly generate new research ideas, building a case and presenting your findings to propel capability forward.
  • You must be willing to embrace change and show flexibility in assignments and the work environment.

About you:

  • You have BSc/BA in Mathematics, Statistics, Engineering, Computer Science or similarly quantitative disciplines.
  • You have 4+ years of experience in Data Science, covering areas such as anomaly detection, predictive analytics, recommender systems, and productionising solutions.
  • You have previous experience in pricing, risk or insurance related roles.
  • You are strongly proficient working with and querying structured data using SQL.
  • You are highly experienced in Python (or R) applied to data analysis and predictive modelling and can write robust and scalable code.
  • You are well-versed in modern machine learning tools and libraries such as Scikit-learn, Tensorflow, Caffe2, PyTorch and Theano.
  • You are familiar with common statistical tools and methods employed in insurance analysis, such as generalised linear models (GLMs), classification and regression trees (CARTs), ensembling methods, and clustering approaches as well as demonstrable knowledge in Bayesian statistics.
  • You have experience and enthusiasm for reproducible research techniques including version control (geg. Git & Github etc.).
  • You have an outstanding eye for detail and take care to make sure that your work is accurate and effective.
  • You have the ability to present complex information in an easily digestible format, appropriate for the audience.
  • You are a lifelong learner; as technologies and techniques are constantly evolving, you are proactively pushing yourself to develop your skills and knowledge.
  • You are resilient to change and use a holistic view of the business to ensure your goals are aligned and your work has impact.

Bonus points:

  • You have a graduate degree in a highly quantitative discipline such as Applied Mathematics, Physics or Computer Science.
  • You have previous experience in a fast-growing scale-up.
  • You have previous experience in the insurance industry.
  • You are comfortable using cloud infrastructure as code to build data pipelines and model deployment services. AWS experience in particular is a plus.
  • You are proficient with Docker and Kubenetes.

Tags: AWS Bayesian Classification Data analysis Data pipelines Docker Engineering Feature engineering Git Machine Learning ML Model deployment Model training Python PyTorch R R&D Recommender systems Research Scikit-Learn SQL Statistics TensorFlow Testing Theano

Perks/benefits: Career development

Regions: Remote/Anywhere Europe
Country: United Kingdom
Job stats:  27  2  0
Category: Data Science Jobs

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