Senior Data Scientist
Role details
Job location
Tech stack
Job description
We are hiring a Senior Data Scientist to join our Data and Insight team in a newly created role. This is a product-facing, experimentation-led machine learning position focused on building high impact models, designing robust simulations and driving measurable business outcomes through rigorous testing and evaluation.
You will report to the Lead Data Scientist and sit within the Data and Insight function. The role is centred on algorithm design, model evaluation and statistical experimentation focussing on product impact.
You will work across multiple areas of the business, translating complex product and commercial challenges into well-structured analytical frameworks, testable hypotheses and high quality predictive models. This role requires someone who is comfortable moving from exploratory analysis through proof of concept to controlled experimentation and risk assessment.
What You Will Do
- Design, develop and refine machine learning models ranging from linear and logistic regression through to tree-based methods, ensemble approaches and advanced algorithms
- Develop proof of concepts and translate exploratory insights into structured modelling approaches
- Design and execute statistical offline simulations to validate modelling approaches prior to live experimentation
- Plan, implement and analyse controlled A/B tests, ensuring statistical robustness and clear interpretation of results
- Define success metrics aligned to business objectives and ensure appropriate evaluation frameworks are in place
- Analyse model performance using appropriate metrics such as precision, recall, ROC-AUC, log loss, calibration measures and model-specific metrics
- Identify potential sources of bias, data leakage and experimental confounding, and proactively mitigate associated risks
- Work closely with Product, Engineering and other stakeholders to prioritise opportunities and ensure models deliver measurable value
- Communicate complex modelling concepts, trade-offs and experimental results in a clear and accessible way to both technical and non-technical audiences
- Contribute to raising the overall standard of modelling practices within the team
Requirements
- 3 to 4 years of experience building, evaluating and iterating on machine learning models using large and complex data sets
- Strong academic background in Statistics, Mathematics, Computer Science or a related quantitative discipline
- Deep understanding of statistics, machine learning and experimental design principles
- Demonstrated experience running A/B tests, designing offline validation strategies and interpreting experimental outcomes
- Strong grasp of model evaluation metrics and the ability to select appropriate performance measures based on business context
- Strong programming skills in Python with experience using libraries such as NumPy, Pandas and related tools for data manipulation and analysis
- Experience working with cloud-based data infrastructure such as BigQuery and AWS services including S3 and SageMaker
- Experience using Jupyter notebooks for exploratory analysis, modelling and communicating findings
- Ability to move comfortably between high level problem framing and detailed quantitative analysis
- Strong product orientation with experience collaborating closely with cross-functional teams
- Excellent written and verbal communication skills, with the ability to explain technical concepts clearly and confidently
Desired Skills and Experience
- Experience working in a two-sided marketplace or similarly complex environment
- Familiarity with ranking metrics and optimisation techniques in high volume marketplace environments
- Practical experience experimenting with large language models and designing evaluation frameworks for generative AI use cases
- Understanding of MLOps principles and the model lifecycle, including deployment, monitoring and retraining considerations
Benefits & conditions
- 25 days of paid holiday, with extra days added at 3 and 5 years of service.
- Fully remote working, plus up to 20 days each year to work from anywhere in the world.
- An annual Learning & Development budget of €550 to spend on courses, training, or other resources that support your professional development.
- Access to Oliva, a leading mental health and wellbeing platform, offering personalised support when you need it.
- A €250 allowance towards essential home office technology to help you stay connected and productive.
Interview Process
- Screening Call with Talent Partner
- 1st Stage - Hiring Manager Stage
- 2nd Stage - Technical Interview (Live case discussion)
- 3rd Stage - Values interview
Diversity Statement
At Bark, we are a platform for people, revolutionising the way professionals and individuals connect since 2014. Our culture is defined by excitement, ambition, and a commitment to raising the bar. We value diversity, equity, inclusion, and belonging (DEIB) and are dedicated to embedding these principles into everything we do. We are committed to fostering an inclusive environment where everyone can thrive, and our focus is on hiring, retaining and developing a globally diverse workforce that is passionate about excelling our platform and supporting our customers succeed. Be part of our dynamic team, where bold ideas thrive, and create a future worth shouting about.
