Data Analyst

Tower Research Capital • New York, NY

14d • $150,000 - $180,000 • Hybrid

About The Position

Tower Research Capital, a leading quantitative trading firm, is seeking a Data Analyst to join its Data team within the Core Engineering department in New York. This role involves contributing to data pipelines, applying AI/ML methods, prototyping prompts and models, implementing validation checks, assisting with new dataset onboarding, and evaluating AI tools for data processing. The analyst will build fluency in financial instruments and market data conventions, take ownership of datasets, and work with modern data tooling to ensure reliability and document processes. The position is in a stimulating, results-oriented environment with highly intelligent and motivated colleagues.

Requirements

• Master’s or PhD in Computer Science, Engineering, Mathematics, Statistics, Physics, Economics, or a related quantitative discipline
• Strong proficiency in Python and SQL. Evidence of this through 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 work in a collaborative research lab or production software setting
• Hands-on experience with machine learning or applied AI through coursework, thesis/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 basic software engineering hygiene (testing, documentation, code review)
• Clear written and verbal communication
• Ability to explain technical and AI-related findings to both engineers and non-technical stakeholders, including limitations and failure modes
• Strong problem-solving skills, intellectual curiosity, and a bias toward getting details right
• Comfortable working in a fast-paced, high-accountability environment

Responsibilities

• Contributing to batch and real-time data pipelines that ingest, cleanse, and normalize structured and unstructured sources (market data, vendor feeds, web scrapes, alternative data)
• Writing and maintaining Python and SQL under the guidance of senior engineers
• Applying AI/ML methods to unstructured and semi-structured sources
• Prototyping prompts, models, and evaluation sets; helping productionize approaches that meet the firm’s accuracy bar
• Implementing and running validation checks, anomaly detection, and reconciliation logic
• Using statistical and ML-based methods to flag outliers and data breaks; investigate root causes and help prevent recurrence
• Assisting with onboarding new datasets: review vendor specs and sample files, map fields to internal models, and help integrate APIs under senior oversight
• Evaluating where LLMs or classical ML can accelerate mapping, documentation, and QA
• Using modern data tooling to monitor jobs, improve reliability, and document processes
• Building fluency in financial instruments, market data conventions, production engineering practices, and responsible use of AI on sensitive financial data
• Taking ownership of well-scoped datasets and processes as you ramp

Benefits

• Generous paid time off policies
• Savings plans and other financial wellness tools available in each region
• Hybrid working opportunities
• Free breakfast, lunch, and snacks daily
• In-office wellness experiences and reimbursement for select wellness expenses (e.g., gym, personal training and more)
• Company-sponsored sports teams and fitness events (JPM Corporate Challenge, Cycle for Survival, Wall Street Rides FAR and more)
• Volunteer opportunities and charitable giving
• Social events, happy hours, treats, and celebrations throughout the year
• Workshops and continuous learning opportunities

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level