Lead Data Analyst

Lead Data Analyst

Full-Time 40000 - 50000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Lead data analysis to drive strategic decisions and empower teams with insights.
  • Company: Join Gopuff, a tech-first company revolutionising convenience shopping.
  • Benefits: Comprehensive health support, stock options, and exciting employee rewards.
  • Other info: Dynamic team culture focused on collaboration and growth.
  • Why this job: Make a real impact in a fast-paced, innovative environment.
  • Qualifications: 5+ years in analytics, strong SQL skills, and a curious mindset.

The predicted salary is between 40000 - 50000 £ per year.

At Gopuff, we don’t just deliver products; we deliver efficiency.

Since 2013, we’ve pioneered the "Instant Needs" category, turning what used to be a 45-minute errand into a 15-minute solution.

We are a tech-first, operationally obsessed engine that is fundamentally changing how the world shops.

Now, we’re looking for a Lead Data Analyst to join the front lines of our Data team.

We value drive over pedigree and ego-less collaboration over competition.

At Gopuff, data is for empowerment, not gatekeeping.

We have zero room for arrogance, but infinite space for curiosity, grit, and a "no job too small" mindset.

If you’re a high-performer who feels stifled by slow-moving corporate machines, this role is for you. You thrive in the "grey area" of ambiguity and are energised by the prospect of leaving a lasting mark on a disruptive industry.

You will

  • Develop innovative measurement and analytical approaches that build our understanding of performance and customers, embedding these learnings into the Category team's day-to-day decision making.
  • Answer complex business questions through detailed quantitative analysis and experimentation, extracting meaningful and actionable insights.
  • Influence both strategic and tactical decision-making in our EU Leadership and Category Management teams through strong communication, and by proactively identifying opportunities for improvement.
  • Act as the main EU partner for our central Analytics & Data Engineering teams to implement reliable & scalable data pipelines that manage & transform the information we need.
  • Build the necessary models and tools to inform our pricing strategies, helping Category Managers maintain a competitive position versus our competitors while maximising margin opportunity.
  • Partner with our Customer Insights team, supporting them with their customer and competitor research projects and helping to embed learnings into the Category teams.
  • Proactively build and nurture a culture of data-driven decision making through coaching & supporting teams to increase their data literacy and confidence
  • Support and mentor the other analysts in the team to help them develop their skills and deliver great results.

You have

  • 5+ years of experience in analytics or data science - preferably in fields related to grocery, trading, marketing, or consumer product.
  • A strong understanding of statistical analysis and experiment design.
  • A Bachelor's Degree in Business, Mathematics, Statistics, or other quantitative discipline is beneficial, but not essential.
  • Expert skills in SQL and databases, able to write structured and efficient queries on large data sets.
  • Experience with dbt is a strong plus, along with Python or R and Github.
  • Development experience with BI platforms such as Looker, Tableau, Power BI. Experience with Looker and Look ML in particular is strongly preferred.
  • A strong and confident communication style, with good knowledge of data visualisation and storytelling.
  • A high degree of curiosity, comfortable gathering and analysing large amounts of data across a variety of business dimensions.
  • The role will be London-based, with the candidate ideally based in/around London or able to come to the office on a regular basis.

Benefits

  • We offer comprehensive medical, dental, vision and Mental health support to all eligible employees.
  • Company RSUs (Restricted Stock Units).
  • Gopuff employee rewards (including some great brand partnership deals).
  • Annual performance appraisal and bonus.

Company Summary & EEOC Statement

At Gopuff, we know that life can be unpredictable.

Sometimes you forget the milk at the store, run out of pet food for Fido, or just really need ice cream at 11 pm.

We get it—stuff happens.

But that’s where we come in, delivering all your wants and needs in just minutes.

And now, we’re assembling a team of motivated people to help us drive forward that vision to bring a new age of convenience and predictability to an unpredictable world.

Like what you’re hearing? Then join us on Team Blue.

Gopuff is an equal employment opportunity employer, committed to an inclusive workplace where we do not discriminate on the basis of race, sex, gender, national origin, religion, sexual orientation, gender identity, marital or familial status, age, ancestry, disability, genetic information, or any other characteristic protected by applicable laws.

We believe in diversity and encourage any qualified individual to apply.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses.

These tools assist our recruitment team but do not replace human judgment.

Final hiring decisions are ultimately made by humans.

If you would like more information about how your data is processed, please contact us.

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Lead Data Analyst employer: goPuff

Gopuff is an excellent employer that values its Operations Associates by offering a dynamic work environment in Cambridge, England, where teamwork and collaboration are at the forefront. With attractive benefits such as holiday pay and ample opportunities for career advancement, employees can thrive both personally and professionally while contributing to a fast-paced and impactful operation.

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Contact Details:

goPuff Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Lead Data Analyst

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like goPuff!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Lead Data Analyst at goPuff.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like goPuff.

Apply Directly through Our Website

When you find a suitable opening like Lead Data Analyst at goPuff, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Lead Data Analyst

Analytical Skills
Statistical Analysis
Experiment Design
SQL
Data Querying
Python
R

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at goPuff, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at goPuff. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at goPuff

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at goPuff!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.