Designing, building, and maintaining scalable batch and real-time data pipelines to ingest, cleanse, and normalize data from a wide variety of structured and unstructured sources (market data, web scrapes, vendors, alternative data)
Designing and productionizing AI/ML workflows for unstructured and semi-structured data, including document/entity extraction, classification, vendor-file parsing, news and filings processing, and alternative-data onboarding
Owning prompt/model selection, evaluation harnesses, human-in-the-loop review, and monitoring so AI-assisted feeds meet the firm’s accuracy and latency standards
Owning core investment data domains, designing and evolving data models for Security Masters, Corporate Actions, and Referential datasets across various asset classes (Equities, Futures, FX, Derivatives)
Evaluating and implementing modern data tooling (SQL, Kafka, Airflow, Cloud) to improve the speed, reliability, and observability of the data ecosystem
Implementing robust validation checks, anomaly detection, and reconciliation logic to ensure "zero-error" data delivery to trading systems
Applying statistical and ML-based methods to detect outliers, drift, and silent data breaks
Partnering directly with Data Scientists and Quants to understand their research needs, prototype data extraction methods (including AI-enabled approaches), and operationalize research signals into production-grade feeds
Managing the end-to-end process of onboarding new datasets, engaging with external vendors to understand data nuances, and integrating APIs
Assessing where AI can accelerate mapping, documentation, and QA without compromising data integrity
Qualifications
3+ years of professional experience in data engineering, preferably within the financial industry (Hedge Fund, Asset Manager, or FinTech)
Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Physics, or a related quantitative discipline
Understanding of financial instruments, financial datasets from Bloomberg, S&P, LSEG
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Tower Research Capital is seeking a Python Developer to build and support a Python data science platform for global trading research. The role covers ETL pipelines, visualization, compute infrastructure, in-house tools,
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
Programming Mastery: Expert-level proficiency in Python (including Pandas, NumPy, and async frameworks) and advanced SQL (complex queries, window functions, performance tuning)
Hands-on production experience applying AI or ML to data problems—such as NLP, information extraction, classification, or LLM-based processing of unstructured data
Ability to evaluate model quality (precision/recall, error analysis, gold-set design), manage failure modes, and ship reliable pipelines rather than one-off prototypes
Familiarity with common AI libraries and APIs (e.g., scikit-learn, PyTorch, Hugging Face, and/or 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 traders and researchers, including limitations and risk
Anticipated annual base salary range USD $230,000 - $250,000 plus eligible for discretionary bonus
Benefits
Tower’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.
Tower Research Capital is an equal opportunity employer.
About Tower Research Capital
Financial Services1,001-5,000Founded 1998
Tower Research Capital is a quantitative trading firm that builds high-performance technology and independent trading teams to trade across global markets and asset classes.