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-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
Anticipated annual base salary range USD $150,000 - $180,000 plus eligible for discretionary bonus
BenefitsTower's headquarters are in the historic Equitable Building, right in the heart of NYC's Financial District and our impact is global, with over a dozen offices around the world.
At Tower, we believe work should be both challenging and enjoyable. That is why we foster a culture where smart, driven people thrive - without the egos. Our open concept workplace, casual dress code, and well-stocked kitchens reflect the value we place on a friendly, collaborative environment where everyone is respected, and great ideas win.
Our benefits include:
- 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
At Tower, you'll find a collaborative and welcoming culture, a diverse team and a workplace that values both performance and enjoyment. No unnecessary hierarchy. No ego. Just great people doing great work - together.
