Senior Data Analyst, Curve
Salary not provided
Offers share options
SQL
Looker
Kafka
Google Analytics
Snowplow
Amplitude
BigQuery
dbt
Senior level
London
Banking platform consolidating cards & accounts
Job no longer available
Banking platform consolidating cards & accounts
201-500 employees
FintechB2CBankingPersonal financePaymentsCredit cards
Job no longer available
Salary not provided
Offers share options
SQL
Looker
Kafka
Google Analytics
Snowplow
Amplitude
BigQuery
dbt
Senior level
London
201-500 employees
FintechB2CBankingPersonal financePaymentsCredit cards
Company mission
Curve is on a mission to simplify the way people spend, send, see and save money.
Role
Who you are
- 5+ years working experience as a data analyst preferably in a growth focused company, fintech, e-commerce, consumer tech startups, financial services or consultancies
- Advantage: Background in behavioural science, psychology, economics, mathematics or statistics
- A passion for data discovery, interpretation and storytelling with experience extracting insights from raw data and converting them into product/business recommendations
- Proven track record of using SQL to manipulate and extract data
- Some familiarity with experiment design and statistical analysis
- Hands-on experience with data warehouse modelling techniques and ELT data pipelines, data catalogues and data models (ideally with dbt)
- Comfortable working with engineers, data engineers and marketing managers to track and attribute customers correctly
- Familiarity with business intelligence and data visualisation tools (ideally Looker)
- Exposure to product teams and familiarity with their ways of working (e.g. Agile)
- Advantage: Experience setting up and maintaining product analytic tools such as Amplitude or Google Analytics
- Flexibility to quickly adapt to changing priorities within a very dynamic startup environment. You will be required to be able to juggle multiple requests - often coming at the last minute
- The ability to work autonomously is important, we operate a lean team so whilst there is plenty of support available to help answer questions, you will not be micromanaged and instead be given the freedom to work towards your own goals and deal directly with stakeholders
- Strong experience building relationships and maintaining trust with senior stakeholders across the business
- Effective and flexible communication skills, including the ability to translate technical detail into business and commercial objectives, and vice versa
- Ability to write research papers that succinctly summarises the issue and provides recommendations to stakeholders
- Proven record of taking proactive action based on your own findings and analysis
- A direct communication style - you’re not afraid to challenge others (including c-level) and speak your mind
What the job involves
- We’re looking for an experienced data analyst who can build strong relationships with stakeholders and executives to identify and explore opportunities our customers will love
- Crucially, you are not just someone who pulls figures or just builds dashboards, you will be adding valuable insight to help drive data-led decisions within the organisation
- Proactiveness rather than reactiveness is the aim of the game
- The ideal candidate is someone who knows how to ask the right questions, yet can work autonomously to deliver upon stakeholder requests
- Someone who has experience in helping to shape company strategy through data utilisation and can measure performance against key metrics is preferred
- Strong technical skills is a must as you will be working closely with the Analytical Engineering team to help model and clean data
- The initial focus for the role will be on growing our customer base, so you will take your lead in day-to-day operations from the Growth Manager, but report functionally to the Head of Analytics who will assist career development and work with you to ensure you stay up to date with the latest analytical developments
- We partner with our data engineering, analytics engineering and machine-learning teams to share the workload of data tracking, modelling and cleaning
- Moreover, we are different from most startup analytics teams in that we spend most of our time in research mode, essentially exploring and interpreting data (the fun stuff!)
- Importantly though you still will need to roll up your sleeves and get into the nitty-gritty of the data to understand where it comes from and what it represents so that you can correctly interpret the output
- This ultimately means that your main focus will be on proactive discovery deep dives, along with recommendations that influence roadmaps and company strategy
- You can expect to be closely involved in the launch of exciting new initiatives, create a pipeline of product opportunities, grow revenue for the company, focus on improving the customer experience, kickstart predictive modelling capabilities and establish processes for the long-term
- You should definitely apply if you’re a well-rounded analyst with strong analytical and technical skills, as well as a business mind and the ability to think critically
- We’re especially looking for curious “doers” who are passionate about deep-dive analysis, experimentation, building relationships with stakeholders across the business, and telling stories through data
- It will be particularly interesting to you if you’re knowledgeable about consumer finance, customer journeys and/or behavioural economics
- Discovery analyses: Proactively identifying discovery opportunities; Interpreting data to develop new revenue streams, optimise propositions and offers and improve the customer experience; Influencing the roadmaps of product/business teams through compelling data storytelling and viable recommendations
- Data manipulation and interpretation: Ability to handle and work with large datasets, clean and preprocess data, and extract meaningful insights from them. Strong SQL skills are a must!
- Data modelling: Working alongside data engineers and analytics engineers to design and build data pipelines, create seamless data models and enable self-service across teams
- Tracking & Attribution: Working with back-end, front-end, DevOps & QA engineers to ensure that our data models are well designed so that we can correctly attribute customers to marketing campaigns and analyse their post-sign up behaviours
- Evangelisation: Helping us implement a data-driven mindset in the company by educating others and building self-service reports
- Mixed methods: Working closely with the marketing, product and data science teams to uncover deeper insights about how our customers interact with the products
- Pioneering: Driving best practices in terms of data quality and code quality
- Working mainly with dbt, Snowplow/Kafka and Looker in a Google Cloud Platform environment (BigQuery, Google Analytics)
Salary benchmarks
Our take
Keeping track of spending across multiple credit and debit cards can be a difficult task. Curve lets customers consolidate all of their bank cards into a single card and app, to make it easier to manage spending and access other benefits.
Curve is following in the footsteps of several European neobanks, including N26, Monzo and Revolut, with ambitious expansion plans for the US. Americans have seven to eight cards on average and they typically love rewards, making the market attractive for Curve.
The company has a track record of responding quickly to consumer wants. For example, it has launched cryptocurrency rewards programs to cater to the ever-growing ‘crypto-curious market', as well as partnering with both Berg Watches and Fidesmo to meet expanding demand for wearable payments. In 2022, Credit Suisse backed a $1 billion credit facility for the company, to enable it to scale its lending business and in 2025, it received £37 million more in funding to help it reach profitability and launch new product ranges.
Steph
Company Specialist at Welcome to the Jungle
Insights
Top investors
Company
Funding (last 2 of 9 rounds)
Mar 2025
$50.3m
LATE VC
Jan 2024
$40.5m
LATE VC
Total funding: $347.2m
Company benefits
- 20 Days Vacation (we actually want you to take this)
- 10 Paid Holidays
- Work from home opportunities
- Competitive salary with employee share options package
- Free Curve Metal subscription for you and +1
- Generous yearly Learning and Development budget
- 10 days per year for training and conferences
- Unlimited book policy
- Life insurance
- Health care cash plan
- Life coaching
- EAP services
- 24/7 GP access
- Annual subscriptions to Calm & FIIT for your mind and body
- Discounted gym membership
- Ride to work scheme
- Nutritionist access
- Discounted shopping vouchers
- Season ticket loan
- Bonus days off for your birthday, moving house and Christmas
- Six nights of Night Nanny for new parents
Company HQ
Paddington, London, UK
Leadership
Shachar Bialick
(Founder & CEO)Was Head of Product at Checkout.com. Founded a number of businesses in Israel, and has an MBA from INSEAD.
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