Our Team
The Data team is a cross-functional team of experienced and passionate data enthusiasts. We use and own modern data tools (Fivetran, Snowflake, dbt, Looker) and cover a diverse range of data problems and stakeholders.
What we're offering you:
- Flexible hours and summer hours
- Competitive holiday benefits (25 days a year paid holiday, plus 8 bank holidays)
- Work from anywhere for 2 weeks a year
- Life Assurance to protect your loved ones
- Benefits allowance for health, dental, and vision coverage
- Defined Contribution Pension and Salary Sacrifice Scheme
- Be Well: Our award-winning wellbeing and mental health programme to support all MVFers and their families
- Family Forward support for our MVF parents and their mini-mes
- Free breakfast when in the office
The Role
MVF is seeking an exceptionally skilled and driven Data Scientist to deliver upon our plans for growth. This is a hybrid-role across Data Science and ML Engineering: we would like someone with either a background in machine learning engineering, but a desire to learn and grow in creating data science products or vice versa.
You will be pivotal in building our Data Science and Machine Learning capabilities in order to hit our strategic goals. These are the problem spaces in our backlog:
- Recommendation systems - predicting cross-sell opportunities
- Imbalanced classification - predicting the value of leads
- Optimisation (e.g., Linear programming) - optimising which leads / products we sell to which client
- Forecasting - predicting client demand
- Experimentation
You will be communicative, commercially-minded, with a strong team-spirit. You will enjoy collaborating with stakeholders, as you will be delivering value across the business, from Paid Marketing to Operations and Sales.
Reporting to the Head of Data, you will collaborate closely with a Senior Data Scientist to deliver upon our roadmap. You will have support from Analytics Engineering teams to build and maintain pipelines and from Software Engineering teams to productionize models. The ideal candidate will relish the opportunity to understand their stakeholders more deeply and define where they think they (and Data Science) can add the most value. With support, they will be excited to build data science models from inception to production.
Responsibilities:
- Build and manage a Machine Learning Platform by selecting and integrating tools that complement the existing data ecosystem (AWS, Snowflake)
- Productionise ML models, ensuring that they are running scalably, efficiently and robustly
- Develop Data Science/Machine Learning products addressing key business needs in accordance with ML best practices
What Success Looks Like:
- Building effective and efficient Data Science models that deliver measurable business value
- Ensuring Machine Learning is executed using best-in-class tools, techniques, and approaches within budget and time constraints
- Ensuring exceptional data integrity and quality across all projects
- Develop ML monitoring and observability pipeline for deployed models
Our Ideal MVF'er:
- 3+ years of experience in a dedicated Data Science/Machine Learning role; additional data or commercial experience is a plus
- Strong understanding of mathematical background, focusing on statistics and linear algebra
- Highly proficient in Python (Pandas, Scikit-Learn, PyTorch, PySpark) and SQL
- Experience with Snowflake (function & procedure) and Snowpark is a plus
- Experience with unit and integration tests
- Strong understanding of machine learning algorithms and best practices
- Vision for MLOps best practices, particularly regarding version control, Docker, MLFlow, CI/CD
- Strong communication skills, with the ability to engage effectively with diverse stakeholders
- Good commercial understanding; knowledge of marketing operations is a bonus
