Jobs / United States / Tower Research Capital LLC
Data Analyst
Tower Research Capital LLC · 🇺🇸 New York
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 44 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 9 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Tower Research Capital LLC paid sponsored hires in similar roles2 certified filings for “Analyst, Operations” (Operations Research Analysts) in SC: $90k–$90k, median $90k. Most were filed at wage level I (100%) — 1 lottery entry, ≈15% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Tower Research Capital LLC
The US Department of Labor certified 44 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 9 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Tower Research Capital LLC →
About the role
Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities. Tower is home to some of the world’s best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization. Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance. At Tower, every employee plays a role in our success. Our Business Support teams are essential to building and maintaining the platform that powers everything we do — combining market access, data, compute, and research infrastructure with risk management, compliance, and a full suite of business services. Our Business Support teams enable our trading and engineering teams to perform at their best. At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential. Our Core Engineering department is seeking a Data Analyst to join our Data team in New York. 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 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 • Hands