At a Glance
- Tasks: Drive predictive analytics to forecast trends and optimise performance.
- Company: Join Pearson, a leader in lifelong learning and educational solutions.
- Benefits: Enjoy 25 days annual leave, flexible working, and a generous pension scheme.
- Why this job: Be part of a dynamic team making impactful data-driven decisions.
- Qualifications: Experience with R programming and strong analytical skills required.
- Other info: Hybrid role based in Salford Quays, accommodating various working patterns.
The predicted salary is between 36000 - 60000 £ per year.
Location: Hybrid working, minimum 2 days in the Manchester (Salford Quays) Office
Reports to: Head of Data
Salary: £50K, plus target bonus of 8%
About Pearson: Learning is no longer just a stage of life but a lifelong journey. In an era where AI is moving at breathtaking pace and where there is huge demand for new talent, with new skills, the world needs learning more than ever before. Whether it’s upskilling in the workplace, developing a team, getting ahead in school, making the grade at university, or learning a new language, millions of people around the world trust Pearson products and services to help them realise the life they imagine through learning. We hold learners, educators, and enterprises at the heart of our thinking. Our five interconnected business divisions work together to meet people’s evolving learning needs. We’re proud to be a trusted partner in the moments that matter throughout their lives.
About UK Assessment & Qualifications: We are responsible for the delivery of nearly 4 million examination results per annum, including A-Level, GCSE, BTEC and T-levels for students in UK and International centres. Our in-house systems process every learner from registration to marking and certification, in a highly regulated business. We currently operate a hybrid estate of predominantly bespoke systems, with an ongoing strategic transformation programme to migrate from on-prem to cloud based, cost effective, scalable and resilient services.
About The Role: We are seeking a talented Data Scientist to drive our predictive analytics capabilities across commercial and operational processes. The successful candidate will apply advanced analytical techniques to forecast trends, optimise performance, and inform strategic decisions. This role will work closely with cross-functional teams to enhance data-driven decision-making and contribute to the continuous improvement of our operations.
Key Responsibilities:
- Predictive Modelling: Develop and implement predictive models to forecast key metrics such as sales performance, customer and learner behaviour, and operational efficiency.
- Data Analysis & Insight Generation: Analyse complex datasets to uncover patterns, trends, and correlations that inform business strategies.
- Operational Optimisation: Use advanced analytics to identify opportunities for improving operational processes, resource allocation, and cost efficiency.
- Commercial Insights: Provide data-driven recommendations to support commercial initiatives, including pricing strategies, market segmentation, and demand forecasting.
- Data Visualisation & Reporting: Create clear and insightful visualisations and reports to communicate findings and predictions to stakeholders.
- Collaboration: Work closely with commercial, operational, and technical teams to understand business challenges and deliver actionable insights.
- Model Evaluation & Maintenance: Continuously monitor, validate, and refine predictive models to ensure accuracy and relevance.
Essential Skills & Experience:
- Preference for ‘R’ programming language but other machine learning languages/tools also acceptable.
- Ability to work under pressure and to tight deadlines and manage own time effectively.
- Ability to solve problems using initiative and a methodical approach to tasks.
- Adaptable and flexible approach and able to prioritise workloads.
- Ability to collate and analyse information from various sources.
Job Location and Hours:
The role is aligned to our office in Salford Quays on a 2 day hybrid basis, working a 37.5 hour week. We work a 37.5 hour week, with all our team free to flex their day around our core hours, which are Monday to Friday, 10 to 4 GMT/BST. School runs, etc can be accommodated. Other flexible working patterns can be considered, including part-time working and non-traditional hours. As we regularly work with global teams, particularly in India and the US, there may be the occasional need to accommodate meetings outside of core hours.
Your benefits and rewards:
- 25 Days annual leave (increasing by 1 day with every year of continuous service up to 30 days); annual leave trading, +/- 5 days.
- Annual Bonus.
- Private Pension plan scheme where we pay in double what you contribute, up to 16% depending on your age.
- Life, private medical and dental care insurance options, plus free eye tests.
- Stock/share purchase options.
- Maternity, paternity, and family care leave as well as flexible working policies.
- An employee wellbeing assistance programme.
- Cycle to work program, volunteering days, gym membership concessions in selected office locations, along with retail and leisure discounts.
Data Scientist (Predictive Analytics Specialist) employer: Pearson - UK
Contact Detail:
Pearson - UK Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist (Predictive Analytics Specialist)
✨Tip Number 1
Familiarise yourself with predictive modelling techniques, especially using the 'R' programming language. Brush up on your skills by working on relevant projects or datasets that showcase your ability to forecast trends and optimise performance.
✨Tip Number 2
Network with professionals in the data science field, particularly those who work in educational assessments or similar industries. Attend meetups or webinars to gain insights into current trends and challenges, which can help you tailor your approach during interviews.
✨Tip Number 3
Prepare to discuss specific examples of how you've used data analysis to drive business decisions. Think about instances where your insights led to operational improvements or commercial success, as these will resonate well with the hiring team.
✨Tip Number 4
Showcase your ability to collaborate with cross-functional teams. Be ready to explain how you've worked with different departments to solve problems and deliver actionable insights, as this is a key aspect of the role at Pearson.
We think you need these skills to ace Data Scientist (Predictive Analytics Specialist)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the Data Scientist role. Focus on your expertise in predictive modelling, data analysis, and any specific programming languages like R.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and how your background fits Pearson's mission. Mention specific projects or experiences that demonstrate your ability to drive predictive analytics.
Showcase Your Analytical Skills: In your application, provide examples of how you've used data analysis to inform business decisions. Highlight any successful predictive models you've developed and the impact they had on previous projects.
Highlight Collaboration Experience: Since the role involves working closely with cross-functional teams, emphasise your experience in collaborative environments. Share instances where you contributed to team projects and how your insights led to improved outcomes.
How to prepare for a job interview at Pearson - UK
✨Showcase Your Predictive Modelling Skills
Be prepared to discuss your experience with predictive modelling, especially using 'R' or other machine learning tools. Bring examples of past projects where you successfully forecasted trends or improved operational efficiency.
✨Demonstrate Data Analysis Expertise
Highlight your ability to analyse complex datasets. Prepare to explain how you've uncovered patterns and trends in previous roles, and how those insights informed business strategies.
✨Emphasise Collaboration Experience
Since the role involves working closely with cross-functional teams, be ready to share examples of how you've collaborated with different departments. Discuss how you communicated findings and recommendations effectively to stakeholders.
✨Prepare for Problem-Solving Scenarios
Expect questions that assess your problem-solving skills. Think of specific instances where you used a methodical approach to tackle challenges under pressure, and be ready to discuss your thought process.