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- Tasks: Transform messy data into reliable intelligence and automate quality checks.
- Company: Join Boam AI, a cutting-edge tech company revolutionising data management.
- Benefits: Competitive pay, equity options, and a fast-paced learning environment.
- Why this job: Make a real impact on customer workflows with your data expertise.
- Qualifications: 1-3 years in data analysis, strong SQL skills, and Python knowledge.
- Other info: Enjoy high ownership and direct feedback in a no-politics team.
The predicted salary is between 36000 - 60000 ÂŁ per year.
Turn chaos into trusted data at high volume and high speed. Boam AI builds managed data agents that transform messy, unstructured signals from public, private, and proprietary sources into structured, reliable, and always up-to-date intelligence on millions of SMBs and enterprises worldwide. These agentic systems power CRMs, data warehouses, AI products, and missionâcritical decisions across the enterprise with strategic partners such as Uber Eats and Toast.
As a Data Analyst, you will help build, improve, and operate the data pipeline that keeps Boam's truth layer fresh at scale. This is not a dashboard role. You will tackle messy inputs across verticals and geographies, automate quality and throughput, and keep pace with fastâgrowing customer demand. You will work across ingestion, validation, transformation, and analysis, partnering closely with ops, engineering, and data/ML. This is a role for someone who wants real ownership early, loves precision, and learns fast in an environment with minimal safety nets.
What Youâll Do
- Own pipeline quality and freshness across core datasets
- Scale ingestion and validation across new geos and verticals
- Build automation that replaces manual checks and rework
- Monitor pipeline health and drive fast rootâcause fixes
- Build SQL outputs that power production customer workflows
- Produce clear analysis that drives product and customer decisions
- Support ingestion and transforms with pragmatic Python tooling
- Turn investigations into shipped improvements customers feel
- Use nextâgen AI tools to improve speed, rigor, and reliability
You Might Be a Fit If...
- 1â3+ years in data analysis, analytics engineering, or similar roles
- Strong SQL and comfort working with messy, realâworld datasets
- Working knowledge of Python for analysis and automation
- Own problems endâtoâend and close loops without handâholding
- Debug systematically and write crisp, structured investigations
- Prefer automation over manual work and scale what you build
- Thrive without heavy process, QA buffers, or endless safeguards
- Motivated by real customer impact, not perfect dashboards
- Excited to work where AI/data is the product, not a side project
Why Boam AI
- Join a noâpolitics, highâtrust, lowâego, highâtalent team
- Work on a differentiated data moat powering topâtier enterprise partners
- High ownership, direct feedback, and steep learning curve from day one
- Real impact: your work shows up in customer workflows quickly
- Topâtier compensation with meaningful equity upside
- Help build the data systems and standards weâll scale to 100x
Our Hiring Process
- Intro Call â Quick conversation to align on role, motivation, and expectations
- Deep Dive â Walk through past work (projects, analyses, datasets) and how you think
- Work Sample â A practical Boamâstyle data task (SQL/Python + reasoning + clear writeâup)
- Founder Conversation â Values, ownership, pace, and how youâd grow with us as we scale
Data Analyst in London employer: Boam AI
Contact Detail:
Boam AI Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land Data Analyst in London
â¨Tip Number 1
Get ready to showcase your skills! When you land that interview, be prepared to discuss your past projects in detail. We want to see how you've tackled messy datasets and automated processes, so have examples ready that highlight your SQL and Python prowess.
â¨Tip Number 2
Donât just talk the talk; walk the walk! If you get a chance to do a work sample, treat it like a mini-project. Show us your thought process, how you debugged issues, and the automation solutions you implemented. This is your moment to shine!
â¨Tip Number 3
Be proactive in your follow-ups! After interviews, drop a quick thank-you note and reiterate your excitement about the role. It shows us you're genuinely interested and keeps you top of mind as we make our decisions.
â¨Tip Number 4
Finally, donât forget to apply through our website! Itâs the best way to ensure your application gets the attention it deserves. Plus, it gives you a chance to explore more about our culture and values before you even step into the interview room.
We think you need these skills to ace Data Analyst in London
Some tips for your application đŤĄ
Show Your Data Skills: Make sure to highlight your experience with SQL and Python in your application. We want to see how you've tackled messy datasets and automated processes in the past, so donât hold back on those details!
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate crisp, structured communication that gets to the point. Remember, weâre looking for someone who can produce clear analysis, so show us you can do that right from the start!
Demonstrate Ownership: We love candidates who take ownership of their work. In your application, share examples of how you've owned problems end-to-end and driven solutions without needing hand-holding. This will resonate with our high-trust environment.
Apply Through Our Website: Donât forget to apply through our website! Itâs the best way for us to receive your application and ensures youâre considered for the role. Plus, it shows youâre keen on joining our team at Boam AI!
How to prepare for a job interview at Boam AI
â¨Know Your Data Inside Out
Before the interview, dive deep into your past projects and analyses. Be ready to discuss specific datasets you've worked with, the challenges you faced, and how you overcame them. This will show your potential employer that you can handle messy data and have a solid grasp of SQL and Python.
â¨Showcase Your Problem-Solving Skills
Prepare to discuss how you've tackled complex problems in your previous roles. Think about instances where you automated processes or improved data quality. Highlight your ability to debug systematically and close loops without needing constant guidance, as this aligns perfectly with what theyâre looking for.
â¨Demonstrate Your Passion for Impact
Make it clear that you're motivated by real customer impact rather than just creating perfect dashboards. Share examples of how your work has directly influenced customer workflows or decision-making. This will resonate well with their focus on practical outcomes.
â¨Be Ready for Practical Tasks
Expect a work sample task during the interview process. Brush up on your SQL and Python skills, and practice writing clear, structured analyses. Being able to demonstrate your technical abilities in a practical setting will give you a significant edge.
