At CloudWalk, we're building the future of financial services with technology at the core. Our Finance team shapes how we fund, scale, and optimize our products, always with a data-driven mindset and a strong connection to the market.
What You'll Do
Analyze, select, and monitor investments in public equities on NYSE and NASDAQ mainly, plus alternative assets like derivatives and options.
Build the models and data tools behind the strategy: statistical tests, scrapers for investor relations filings, pipelines for market data (prices, fundamentals, filings from providers like Polygon, LSEG, and SEC EDGAR), and a data lake the team can query.
Test investment signals and run backtests with a portfolio simulator that accounts for real trading costs.
Build and maintain end-to-end systems for the fund: execution, reconciliation, risk, and performance reporting (using Python, SQL, Excel, broker APIs).
Use AI tools to sharpen analysis, productivity, and insights.
What You'll Need to Succeed
Python and working knowledge of SQL.
Experience building data pipelines, scrapers, or API integrations, from work, personal projects, or competitions.
Financial-market knowledge: you've competed in investment competitions, financial-market
leagues, or hackathons, or built your own tools for analysis and trading.
Comfort with data analysis: you know when a result is too good to be true.
High agency: you take ownership and move things forward on your own.
Adaptability and comfort in a fast-changing environment.
Genuine interest in financial markets and in using AI in your daily workflow. You don't need market experience, you need curiosity to learn it fast.
Upper-intermediate to advanced English.
Nice to Have
1+ year of experience in financial markets, preferably in public equities (bonus if in the US market) and quantitative strategies (edited)
Certifications completed or in progress (e.g., CFG, CGA, CPA-20, CEA, or CFA).
Experience with cloud data stacks (e.g., AWS, GCP, BigQuery) and pipeline orchestration.
Experience with financial or market data (tick data, fundamentals, filings).
Backtesting or quant work: Kaggle competitions, trading bots, portfolio tools you built yourself.
Experience at fintechs, funds, brokerages, or data-heavy companies.
