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For Companies At a Glance
- Tasks: Transform complex data into actionable insights and support decision-making across teams.
- Company: Join a dynamic company eager to leverage data for smarter business strategies.
- Benefits: Enjoy competitive pay, bonuses, private healthcare, and flexible working options.
- Why this job: Be part of a supportive team that values data-driven decisions and encourages innovation.
- Qualifications: Background in data science or analytics with strong SQL and Python or R skills required.
- Other info: Hybrid role with 2 days in the office, located in West London.
The predicted salary is between 60000 - 80000 £ per year.
Hybrid - 2 Days office based
Location - W.London
Salary - £70k-£80k
Bonus - Discretionary
The Role
You’ll be the go-to person for turning complex data into something useful. Whether that’s spotting customer trends, helping optimise marketing spend, improving the product funnel, or figuring out what we should be doing next. We’re not short of data or tools, but we are looking for someone who can help us make smarter decisions, faster. You’ll work closely with product, marketing, leadership, and our technical teams, translating analysis into action across the business. This is a role for someone who enjoys thinking beyond the dashboard, someone who’s just as comfortable building models as they are explaining them to non-technical stakeholders.
What You’ll Be Doing
- Working closely with our existing data and engineering teams to build on what’s already in place
- Digging into user journeys, customer behaviour, marketing performance, and commercial data
- Developing segmentation, predictive models, and other approaches to surface meaningful insights
- Running experiments and testing ideas to see what actually works
- Supporting teams across the business to make decisions based on data, not hunches
- Spotting opportunities to use data in ways we haven’t thought of yet
What We’re Looking For
- A background in data science, analytics, or a related role, ideally with B2C or B2B2C experience
- Someone who’s worked in travel, retail, or SaaS would be a strong fit, but we’re open
- Strong SQL and Python or R skills
- Comfortable using tools like Tableau, Power BI, or Looker to bring data to life
- Confident working with marketing and customer data – especially if you’ve worked alongside commercial teams before
- You don’t just answer questions, you find the right ones to ask
Bonus Points For
- Experience with A/B testing and experimentation
- Familiarity with tools like Google Analytics, Mixpanel, or CRM platforms
- Exposure to forecasting or modelling customer lifetime value
Why This Role?
- You’ll get to work in a business that’s ready to do more with its data – and wants your help to shape what that looks like
- There’s real support and buy-in for data-led thinking across the company
- You’ll have the freedom to try things, test ideas, and make a visible impact
- You’ll join a friendly, ambitious team that’s growing fast and moving quickly
- Competitive pay, bonus, private healthcare, flexible working, and a genuinely collaborative culture
Data Science Business Analyst employer: KennedyPearce Consulting
Contact Detail:
KennedyPearce Consulting Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Business Analyst
✨Tip Number 1
Network with professionals in the data science and analytics field, especially those who have experience in B2C or B2B2C sectors. Attend industry meetups or webinars to connect with potential colleagues and learn about their experiences at companies like StudySmarter.
✨Tip Number 2
Familiarise yourself with the tools mentioned in the job description, such as SQL, Python, Tableau, and Power BI. Consider taking online courses or working on personal projects that showcase your ability to turn complex data into actionable insights.
✨Tip Number 3
Prepare to discuss your previous experiences where you’ve successfully collaborated with marketing and commercial teams. Think of specific examples where your data-driven insights led to significant business decisions or improvements.
✨Tip Number 4
Stay updated on the latest trends in data science and analytics, particularly in the travel, retail, or SaaS industries. This knowledge will help you demonstrate your understanding of the market and how you can contribute to StudySmarter's goals.
We think you need these skills to ace Data Science Business Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, analytics, and any specific tools mentioned in the job description, such as SQL, Python, or Tableau. Use keywords from the job listing to ensure your application stands out.
Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about data-driven decision-making. Mention specific examples of how you've used data to influence business outcomes, particularly in B2C or B2B2C contexts, as this aligns with what the company is looking for.
Showcase Your Technical Skills: Include a section in your application that details your proficiency with tools like Power BI, Looker, or Google Analytics. If you have experience with A/B testing or customer lifetime value modelling, make sure to highlight these skills as they are considered bonus points.
Demonstrate Your Problem-Solving Ability: Use your application to illustrate how you approach complex problems. Provide examples of how you've identified the right questions to ask and how your insights led to actionable results, especially in marketing or product optimisation.
How to prepare for a job interview at KennedyPearce Consulting
✨Showcase Your Analytical Skills
Be prepared to discuss specific examples of how you've turned complex data into actionable insights. Highlight your experience with SQL, Python, or R, and be ready to explain your thought process when building models or running experiments.
✨Understand the Business Context
Research the company and its industry before the interview. Familiarise yourself with their products, marketing strategies, and customer base. This will help you tailor your answers and demonstrate how your skills can directly benefit their business.
✨Communicate Clearly with Non-Technical Stakeholders
Practice explaining technical concepts in simple terms. Since you'll be working closely with non-technical teams, being able to convey your findings clearly and effectively is crucial. Prepare to give examples of how you've done this in the past.
✨Prepare for Scenario-Based Questions
Expect questions that ask you to solve hypothetical problems or analyse case studies. Think about how you would approach different scenarios related to user journeys, customer behaviour, or marketing performance, and be ready to share your reasoning.
