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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 high-trust work environment.
- Why this job: Make a real impact with your work in a fast-paced, innovative setting.
- Qualifications: 1–3 years in data analysis, strong SQL skills, and Python knowledge.
- Other info: High ownership and steep learning curve from day one.
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 mission‑critical 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’ll tackle messy inputs across verticals and geographies, automate quality and throughput, and keep pace with fast‑growing customer demand. You’ll 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 You’ll 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 root‑cause 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 next‑gen AI tools to improve speed, rigor, and reliability
You Might Be a Fit If...
- 1–3+ years in data analysis, analytics engineering, or similar roles
- Strong SQL and comfort working with messy, real‑world datasets
- Working knowledge of Python for analysis and automation
- Own problems end‑to‑end and close loops without hand‑holding
- 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 no‑politics, high‑trust, low‑ego, high‑talent team
- Work on a differentiated data moat powering top‑tier enterprise partners
- High ownership, direct feedback, and steep learning curve from day one
- Real impact: your work shows up in customer workflows quickly
- Top‑tier compensation with meaningful equity upside
- Help build the data systems and standards we’ll scale to 100x
Our Hiring Process
- Intro Call – Quick conversation to align on role, motivation, and expectations
- Deep Dive – Walk through past work (projects, analyses, datasets) and how you think
- Work Sample – A practical Boam‑style data task (SQL/Python + reasoning + clear write‑up)
- Founder Conversation – Values, ownership, pace, and how you’d grow with us as we scale
Data Analyst employer: Boam AI
Contact Detail:
Boam AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst
✨Tip Number 1
Get familiar with the company and its products before your interview. Knowing how Boam AI transforms messy data into reliable intelligence will help you connect your skills to their needs. Plus, it shows you're genuinely interested!
✨Tip Number 2
Prepare to discuss your past projects in detail. Be ready to explain how you've tackled messy datasets and automated processes. This is your chance to showcase your problem-solving skills and how you own challenges end-to-end.
✨Tip Number 3
Practice SQL and Python tasks that are relevant to the role. You might be asked to complete a work sample, so brush up on your coding skills and think about how you can apply them to real-world scenarios at Boam.
✨Tip Number 4
Don’t forget to highlight your passion for making a real customer impact. Boam values team members who thrive in fast-paced environments and prefer automation over manual work, so let that enthusiasm shine through in your conversations!
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
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 don’t hold back on those details!
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate crisp, structured communication, so make sure your points are easy to follow and get straight to the heart of your experience and skills.
Demonstrate Ownership: We love candidates who take ownership of their work. Share examples of how you've managed projects from start to finish, solved problems independently, and made a real impact in your previous roles.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, we can’t wait to see what you bring to the table!
How to prepare for a job interview at Boam AI
✨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 familiarity with messy data and your problem-solving skills.
✨Showcase Your SQL Skills
Prepare to demonstrate your SQL prowess during the interview. Brush up on complex queries and be ready to explain your thought process when building SQL outputs. Practising common SQL tasks can help you feel more confident and articulate your approach clearly.
✨Emphasise Automation and Efficiency
Since this role values automation over manual work, come prepared with examples of how you've automated processes in the past. Discuss any Python tools you've used for analysis and how they improved efficiency. This will highlight your proactive mindset and ability to scale solutions.
✨Be Ready for Real-World Scenarios
Expect practical questions that reflect the fast-paced environment at Boam AI. Think about how you would handle messy inputs or monitor pipeline health. Being able to articulate your systematic debugging approach will demonstrate your readiness for ownership and real customer impact.
