Hiring: Data Analyst Company: Tower Research Capital Location: New York, United States Job Posted Time: 2026-09-16 21:39:35 Employment Type: Internship / Hybrid Target Skills & Keywords : AWS, Airflow, BigQuery, Dagster, Data Pipeline, Databricks, FPGA, GCP, Git, LLM, Linux, Machine Learning, NLP, Python, Risk Management, SQL, Snowflake, scikit-learn About the job Experience: •25+ year track record of innovation and a reputation for discovering unique market opportunities. Required Skills: •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 Qualifications: •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 •Applied hands-on capability in 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 Compensation: •Generous paid time off policies Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!