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Senior Pricing Data Scientist

OneFamily
Brighton and Hove, UK
18 days ago
Apply on www.collegerecruiter.com
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Job source
www.collegerecruiter.com

Tech stack

Statistical Hypothesis Testing Machine Learning Build Management

Job description

  • Build and deploy retail pricing, demand, lapse, cross-sell and optimisation models.
  • Lead strategic pricing initiatives and fast-turnaround tactical solutions.
  • Collaborate with Product, Protection and Distribution teams to deliver commercial pricing improvements.
  • Communicate insights clearly to technical and non-technical audiences.
  • Ensure rigorous QA, governance and best-practice modelling standards.

Requirements

  • Strong understanding of retail pricing, elasticity, price testing and customer behaviour drivers.
  • Advanced skills in machine learning, modelling, evaluation and optimisation techniques.
  • Solid mathematical and statistical knowledge (GLMs, regression, PCA, time-series, hypothesis testing, etc.).
  • Experience with Protection products (Term Assurance, Critical Illness, Income Protection) and pricing assumptions.
  • A track record of mentoring analysts and data scientists.
  • Commercial awareness, integrity and excellent communication skills., Ambitious, analytical and collaborative - someone who combines technical expertise with commercial insight. You’re principled, courageous and effective; aligned with our values and committed to doing the right thing for our customers.

Apply for this position

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

Moments

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5:11 min

Integrating flat external dependencies without build management tools

Jens Knipper Jens Knipper · Europe 2026 Virtual

2:36 min

Applying supervised machine learning for practical rule extraction

Katja Träumner

2:18 min

Introduction to data science applications in the retail sector

Julian Joseph · LIVE

36 sec

Frustrations with the complexity of modern web development

Andrew Taylor · Coffee With Developers

1:57 min

Evolution of machine learning algorithms and computing hardware

Alexandra Waldherr · LIVE

2:12 min

Framing the customer anomaly detection use case

Lukas Kölbl · LIVE

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LIVE • over 4 years ago

Introduction to Azure Machine Learning

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Anomaly Detection - Using unsupervised Machine Learning for detecting anomalies in customer base

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World Congress 2021 • about 5 years ago

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World Congress 2022 • over 4 years ago

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