Data Scientist

Openr
City of London
2 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist (NLP & LLM Specialist)

Data Scientist - Measurement Specialist

Data Scientist, United Kingdom - BCG X

Data Scientist, United Kingdom - BCG X

Join to apply for the Data Scientist role at Openr


Get AI-powered advice on this job and more exclusive features.


About the Job

Openr is a SaaS platform that transforms how the hospitality industry manages and shares data. By centralising & mastering all recipe, product and pricing in a single platform, we enable hospitality businesses to seamlessly publish consistent & accurate data across all their platforms in real time, including delivery channels, EPOS and other customer touchpoints.


We’ve already achieved significant ARR, closed a £3m fundraise, and are backed by Azzurri Group, one of the UK’s most successful hospitality investment platforms. With an exciting roadmap to deliver, we’re looking for a Data Scientist to help us build price modelling & optimisation for the hospitality sector, enabling brilliant restaurants, pubs, bars & cafés to thrive and grow.


Location & Type

London (Hybrid, 2 days/week)


Type: Full-time


Level: Senior, Mid


What You’ll Do

  • Develop, implement, and maintain advanced price modelling & price optimisation algorithms.
  • Analyse historical and real‑time data to identify pricing opportunities and challenges.
  • Build predictive models to forecast customer behaviour and demand elasticity.
  • Collaborate with engineering teams to integrate algorithms into production systems.
  • Monitor and refine pricing models based on real‑world performance and feedback.
  • Enable Openr customers to conduct A/B testing and scenario simulations using our platform to evaluate the impact of pricing strategies.
  • Conduct research with customers & stakeholders and present insights and recommendations in a clear and actionable manner.
  • Train & upskill your peers, sharing best practice and learnings with the wider team.

What We’re Looking For

  • Previous experience in implementing large-scale price optimisation systems.
  • Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, Economics, or a related field.
  • Strong programming skills in Python, R, or a similar language.
  • Proficiency in data manipulation and analysis tools.
  • Experience with machine learning frameworks and optimisation techniques.
  • Solid understanding & experience of pricing strategies, demand modelling, and elasticity.
  • Strong problem‑solving skills and ability to work with complex datasets.
  • Excellent communication skills and ability to convey technical concepts to non‑technical stakeholders.
  • Experience in e‑commerce, SaaS, or a related industry.
  • Familiarity & experience with AWS.
  • Knowledge of statistical modelling and time‑series forecasting.

What Success Looks Like

  • Implementation of pricing algorithms that enable our customers to sustainably grow their revenue through price optimisation without requiring their own data science capability.
  • Building trust in customers to use machine learning and data science in their pricing decisions as a matter of course.
  • Delivery of scalable, high‑performance pricing models that are responsive to real‑time data and adapt seamlessly to changes in market dynamics.
  • Building strong partnerships with product, engineering, sales & customer success teams, and effectively communicating data science recommendations to influence strategic decisions.
  • Demonstrating a commitment to experimentation, learning, and iterative improvement, ensuring pricing models remain cutting‑edge and competitive.
  • Enhanced customer experience and satisfaction through fair and optimised pricing, coupled with stakeholder trust in the reliability of the pricing systems.

Why Join Openr

  • Market traction: Backed by Azzurri Group, we recently raised £3m in funding.
  • High impact: As our first data science hire, you’ll shape Openr’s growth strategy and success.
  • Autonomy & ownership: You will have freedom to recommend systems, build processes, and set the standard for data science at Openr.
  • Innovative culture: Join an engaged, open, and hard‑working team at the forefront of hospitality tech.
  • Inclusive environment: Join an inclusive culture that welcomes and values all employees.

Role Details

Hybrid Role: At least 2 days/week in our London office.


If you’re an ambitious data scientist ready to take ownership, deliver growth, and lay the foundations for a platform that we believe will truly transform the hospitality sector, we’d love to hear from you!


Application

Referrals increase your chances of interviewing at Openr by 2x. Get notified about new Data Scientist jobs in London, England, United Kingdom. London, England, United Kingdom – 2 weeks ago.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

Education

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.