Data Science Analyst

Vermelo RPO • TRAFFIC • Cambridgeshire, Peterborough, United Kingdom • 1d ago

Job Title: Data Science Analyst

Location: Peterborough (hybrid working - 2 days in office)

We have an exciting opportunity at Markerstudy Distribution (part of Markerstudy Group) for a Data Science Analyst. You will be responsible for providing data science and analytics solutions that helps to shape our strategic roadmaps and customer propositions, working with a variety of teams and stakeholders to embed your findings.Our Data Science and Pricing team provides value in showcasing the business how to monetise data, we are a team of 80 and growing Data Science and Pricing analytical professionals working with every corner of our commercial business. This role sits in the Data Science team. The Data Science team provides data products, insights and services to internal / external stakeholders from partnerships, insurers, customer insight, digital, marketing and call centre teams.

This is a great springboard opportunity for you to start your career in Data Science, we'll provide you with the relevant technical training around our data asset and technology plus more, all we ask is that you're naturally inquisitive, passionate about problem solving and data, and view it as a vocation. You'll fit right into our environment with likeminded peers. As part of your Data Science career, you will be expected to develop and understand a wide range of modern statistical, machine learning and data science methods. This knowledge will be applied to a wide range of business problems, adding demonstrable commercial value.Key Roles and Responsibilities

Explore large structured/ unstructured data from a variety of sources
Explore, distil and visualise data using leading tools and technology
Build strong, collaborative relationships with stakeholders across Markerstudy Distribution and Group
Maintenance of our Data Products, Frameworks and Tools
Drive commercial benefit and solve business problems using data
Understand End-to-End Data Science / Product lifecycle
Working with other Data Scientists & Managers, analytics professionals on Projects

What you can expect to be working on:

Within the first 3-6 months you will gain knowledge of our data assets by creating actionable business insight from our data warehouse to build a strong foundation. Expect to be hands on using tools like Python / SQL, and working with large datasets.
By the end of your first year, you will be competent in Python programming, our tools and framework, and will have undertaken at least one machine learning project. You will have started to create a network of stakeholders.
By month 24 you will have had the opportunity to work on a wide variety of data products e.g. Fraud, Claims, Debt, Digital personalisation. You will be skilled in Python (including real time coding) and SQL.
Throughout you will receive ongoing personal development with senior members of the team to advance your skills and guide your future career progression.

Key Skills, Experience and Knowledge:

Passionate and curious about data science, data. Love solving problems.
Strong numerical, a solid understanding of mathematical concepts and principles.
Strong communication skills, and the ability to "story-tell" to our stakeholders and customers, can adapt for audiences of varying technical abilities.
Resilience, can work independently to deliver projects.
Proactively share insights, results and identify risks with the rest of the team.
Proficient at communicating results in a concise manner both verbally and written.
Experience using an analytical tool/language (Python, R or equivalent) or SQL (advantageous)
Hands-on experience of data analysis and communicating findings (advantageous)
Hands-on experience in the cloud platform and tools i.e. Azure, Databricks (advantageous)

Behaviours:

Team player
Self-motivated with a drive to learn and develop
Logical thinker with a professional and positive attitude
Passion to innovate and improve processes
Value differences and people from all walks of life, both colleagues and customers

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