Data Analyst
The Data Analyst at Confidential Client contributes to building and maintaining batch and real-time data pipelines for diverse financial and alternative data sources. The role involves applying AI/ML techniques, including LLMs, to process unstructured data, performing data validation and anomaly detection, and collaborating closely with senior engineers to integrate and improve data workflows. This position offers the opportunity to develop expertise in financial instruments and cutting-edge data engineering practices within a high-performance quantitative trading environment.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Financial Services.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
Responsibilities
- Contribute to batch and real-time data pipelines that ingest, cleanse, and normalize structured and unstructured sources (market data, vendor feeds, web scrapes, alternative data).
- Write and maintain Python and SQL under the guidance of senior engineers.
- Apply AI/ML methods to unstructured and semi-structured sources; prototype prompts, models, and evaluation sets and help productionize approaches that meet accuracy standards.
- Implement validation checks, anomaly detection, and reconciliation logic.
- Use statistical and ML-based methods to flag outliers and data breaks; investigate root causes and help prevent recurrence.
- Assist onboarding new datasets: review vendor specs and sample files, map fields to internal models, and help integrate APIs under senior oversight.
- Evaluate where LLMs or classical ML can accelerate mapping, documentation, and QA.
- Use modern data tooling to monitor jobs, improve reliability, and document processes.
- Build fluency in financial instruments, market data conventions, production engineering practices, and responsible use of AI on sensitive financial data.
- Take ownership of well-scoped datasets and processes as you ramp.
Qualifications
- Master’s or PhD in Computer Science, Engineering, Mathematics, Statistics, Physics, Economics, or a related quantitative discipline.
- Strong proficiency in Python and SQL — demonstrated via coursework, thesis/research code, internships, or personal projects.
- Internship or research experience involving data engineering, quantitative research, market data, or financial datasets.
- Practical experience with LLMs for unstructured data processing (document/entity extraction, classification, summarization) and with evaluation harnesses or human-in-the-loop review.
- Coursework or project experience with workflow tools (Airflow, Dagster), cloud platforms (AWS/GCP), or warehouses (Snowflake, BigQuery, Databricks).
- Exposure to financial instruments, market microstructure, or vendor datasets (Bloomberg, S&P, LSEG).
- Prior collaboration in a research lab or production software setting.
- Hands-on machine learning or applied AI experience through coursework, research, internships, or projects.
- Comfortable with at least one of: classical ML (scikit-learn or similar), NLP, or LLMs (prompting, evaluation, structured extraction).
- Demonstrated ability to work with messy, large, or imperfect datasets: cleaning, validating, summarizing, and drawing defensible conclusions.
- Familiarity with Linux or Windows command line, version control (Git), and software engineering hygiene (testing, documentation, code review).
- Clear written and verbal communication; able to explain technical and AI-related findings (including limitations and failure modes) to non-technical stakeholders.
- Strong problem-solving skills, intellectual curiosity, and a bias toward getting details right.
Compensation & Benefits
- Anticipated annual base salary range: USD $150,000 - $180,000; eligible for discretionary bonus.
- Generous paid time off policies and hybrid working opportunities.
- Savings plans and other financial wellness tools.
- Free breakfast, lunch, and snacks at the office; in-office wellness experiences and reimbursements for select wellness expenses.
- Company-sponsored sports and fitness events, volunteer opportunities, social events, and continuous learning/workshops.
Confidential Client complies with applicable pay transparency laws. The posted base salary range reflects a good-faith pay range for this position in New York, NY.
Work Location & Eligibility
- Location: New York, NY (on-site / hybrid as determined by the hiring team).
- Applicants must be legally authorized to work in the United States. Confidential Client may conduct background checks as permitted by law.
Why Join
- Work with top quantitative and engineering talent on a high-performance data platform.
- Hands-on experience applying LLMs and ML methods to market and alternative datasets.
- Opportunity for rapid technical growth and ownership of production data systems.
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
If you have questions about how your data is used, please contact us directly.
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