Senior Data Scientist Net Revenue & Revenue Growth Management
Role details
Job location
Tech stack
Job description
- Develop, evolve, and enhance data science models across multiple business areas.
- Lead a team of data scientists across several workstreams using rule-based methods, supervised and unsupervised learning, forecasting, and optimisation techniques.
- Work closely with product owners, data engineers, and ML engineers to deliver high-quality, scalable ML solutions.
- Prepare, clean, and engineer datasets for training and validating machine learning models.
- Define and implement performance metrics, including both ML performance and computing resource usage (CPU/memory).
- Support end-to-end deployment of machine learning models, including monitoring, retraining pipelines, and life cycle management.
- Leverage third-party and syndicated data to generate insights relating to trade promotions, pricing, distribution, and digital shelving-particularly in joint business planning environments.
- Design and execute statistical models and multi-variate tests to measure the impact of business decisions and market variations.
Teamwork & Leadership
- Foster a highly collaborative team culture built on openness, ownership, and accountability.
- Partner with key stakeholders and influence decision-making across the business.
- Contribute to building foundational AI assets across forecasting, optimisation, segmentation, attribution modelling, and experimentation.
- Conduct code reviews and ensure exceptionally high standards in code quality.
- Mentor and support junior data scientists and apprentices.
- Promote responsible AI practices and strong governance.
Requirements
We are looking for an experienced Senior Data Scientist with expertise in Net Revenue Management/Revenue Growth Management, ideally in the CPG or Retail sectors. The Data Scientist is required to lead advanced analytics initiatives across Commercial, Marketing, and Digital workstreams. This role offers the opportunity to guide a high-performing team, shape data science strategy, and deliver impactful, production-ready machine learning solutions.
We are looking for expertise and prior experience with Net Revenue Management/Revenue Growth Management and advanced experience of the below key areas:
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Causal inference
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Intervention analysis
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Counterfactual estimation, Qualifications & Skills for the Senior Data Scientist - Net Revenue Management/Revenue Growth Management
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MS or PhD in Data Science, Computer Science, Applied Mathematics, Statistics, or a similar quantitative discipline is highly desirable.
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Industry experience ideally in CPG/Retail in developing machine learning models and building end-to-end ML pipelines.
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Experience of machine learning algorithms, statistical modelling, and probabilistic programming.
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Expert programming ability in Python, R, and SQL, with deep experience in time series modelling.
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Understanding of forecasting methods: ARIMA, ETS, Prophet, time series pattern detection, and ML-based forecasting.
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Advanced experience in:
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Causal inference
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Intervention analysis
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Counterfactual estimation
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Mathematical optimisation
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Scenario simulation
Solid grounding in Bayesian methods and probabilistic programming.
Hands-on experience with scikit-learn, PyMC, TensorFlow, PyTorch, Databricks ML, Keras, and ML at scale.
Experienced Data Scientist, including leadership experience and demonstrable impact-ideally within a Net Revenue Management/Revenue Growth Management environment.
Critical thinking, exceptional attention to detail, and the ability to collaborate effectively in cross-functional teams.
