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About the Role

Tower Research Capital is seeking a Senior Data Analyst to join their Data team in New York. This role involves designing, building, and maintaining data pipelines, productionizing AI/ML workflows, and managing core investment data domains to ensure high-quality data delivery to trading systems.

Responsibilities

Design, build, and maintain scalable batch and real-time data pipelines for data ingestion, cleansing, and normalization.
Design and productionize AI/ML workflows for unstructured and semi-structured data, including document/entity extraction, classification, and parsing.
Own prompt/model selection, evaluation harnesses, human-in-the-loop review, and monitoring for AI-assisted feeds.
Own core investment data domains, designing and evolving data models for Security Masters, Corporate Actions, and Referential datasets.
Implement robust validation checks, anomaly detection, and reconciliation logic for zero-error data delivery.
Apply statistical and ML-based methods to detect outliers, drift, and silent data breaks.
Partner with Data Scientists and Quants to understand research needs, prototype data extraction methods, and operationalize research signals.
Manage the end-to-end process of onboarding new datasets, engaging with vendors, and integrating APIs.
Assess where AI can accelerate mapping, documentation, and QA without compromising data integrity.

Requirements

3+ years of professional experience in data engineering, preferably within the financial industry.
Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Physics, or a related quantitative discipline.
Understanding of financial instruments and financial datasets from Bloomberg, S&P, LSEG.
Experience with distributed computing frameworks like Spark or streaming technologies like Kafka.
Proficiency in C++, Java, or Rust is a strong plus.
Experience with retrieval-augmented generation, vector search, fine-tuning or distillation, LLM evaluation frameworks, or agentic workflows for data operations.
Prior work applying AI to financial documents, corporate actions, or alternative data.
Expert-level proficiency in Python (including Pandas, NumPy, and async frameworks) and advanced SQL.
Hands-on production experience applying AI or ML to data problems (NLP, information extraction, classification, LLM-based processing).
Ability to evaluate model quality, manage failure modes, and ship reliable pipelines.
Familiarity with common AI libraries and APIs (e.g., scikit-learn, PyTorch, Hugging Face, LLM APIs).
Strong hands-on experience with workflow orchestration tools such as Airflow, Dagster, or similar.
Proven experience building data platforms on AWS / GCP and modern data warehouses (e.g., Snowflake, BigQuery, DataBricks).
Understanding of dimensional modeling, SCD strategies, data partitioning, and VLDB design principles.
Experience with Linux and Windows operating systems, NFS, S3, and work management platforms (JIRA, Confluence, etc.).
Excellent problem-solving skills with a sense of ownership.
Ability to communicate technical and AI-related concepts effectively to non-technical stakeholders, including limitations and risk.

Skills

Python
Pandas
NumPy
async frameworks
SQL
Spark
Kafka
C++
Java
Rust
retrieval-augmented generation
vector search
fine-tuning
distillation
LLM evaluation frameworks
agentic workflows
NLP
information extraction
classification
LLM-based processing
scikit-learn
PyTorch
Hugging Face
LLM APIs
Airflow
Dagster
AWS
GCP
Snowflake
BigQuery
DataBricks
dimensional modeling
SCD strategies
data partitioning
VLDB design
Linux
Windows
NFS
S3
JIRA
Confluence

Location

New York

Work Type

Hybrid

Experience Level

Senior

Education Level

Bachelor's degree
Master's degree

Salary/Compensations

USD $230,000 - $250,000 plus eligible for discretionary bonus

Benefits

Generous paid time off policies
Savings plans and other financial wellness tools
Hybrid working opportunities
Free breakfast, lunch, and snacks daily
In-office wellness experiences and reimbursement for select wellness expenses
Company-sponsored sports teams and fitness events
Volunteer opportunities and charitable giving
Social events, happy hours, treats, and celebrations
Workshops and continuous learning opportunities

About the Company

Tower Research Capital is a leading quantitative trading firm founded in 1998, built on a high-performance platform and independent trading teams with a 25+ year track record of innovation.
Tower empowers portfolio managers to build teams and strategies independently while providing economies of scale.
Engineers develop electronic trading infrastructure, solving challenging problems in low-latency programming, FPGA technology, hardware acceleration, and machine learning.
Ongoing investment in engineering talent and technology ensures their platform remains unmatched.
Business Support teams are essential to building and maintaining the platform that powers everything, enabling trading and engineering teams to perform at their best.
Employees find a stimulating, results-oriented environment where colleagues inspire each other.
Tower's headquarters are in the historic Equitable Building in NYC’s Financial District, with a global impact.
The company fosters a culture where smart, driven people thrive without egos, valuing a friendly, collaborative environment.
Tower offers a collaborative and welcoming culture, a diverse team, and a workplace that values both performance and enjoyment, with no unnecessary hierarchy or ego.

Equal Opportunity

Tower Research Capital is an equal opportunity employer.