Описание

We are a data-driven algorithmic trading firm building systematic trading strategies for financial markets. Our work combines financial market research, data analysis, backtesting, and practical strategy development. Because this field is still developing in Azerbaijan, this role offers a unique opportunity for someone who wants to work at the intersection of large-scale data engineering, financial markets, and quantitative research.

Responsibilities

Design, build, and maintain data pipelines that collect, clean, validate, and store large volumes of market data
Own data quality: gap detection, deduplication, timestamp integrity, reconciliation between sources, and automated validation
Profile and optimize performance-critical code through vectorization, memory layout, chunking, JIT compilation, parallelism, and efficient storage formats
Build and maintain the datasets and feature sets used for backtesting and machine learning
Support machine learning work end to end: feature engineering, dataset preparation, training and evaluation pipelines, and protection against data leakage
Analyze data independently, apply statistical and mathematical methods, look for patterns, and bring hypotheses and proposals to the research team
Write clean, tested, reproducible Python following solid engineering practices (modular design, version control, code review, documentation)
Design SQL schemas, write complex queries, and optimize them
Research new tools, libraries, and approaches, evaluate them honestly, and propose the ones worth adopting
Communicate findings clearly to both technical and non-technical team members

Requirements

Bachelor’s degree in computer science, engineering, mathematics, statistics, data science, or a related quantitative discipline
At least 2 years of professional experience in data engineering, software engineering, data science, or a similar field
Strong analytical thinking and genuine enjoyment of mathematical methods, exploring data, and doing research (the single most important criterion for us)
Solid software engineering fundamentals: data structures, algorithms, complexity analysis, clean and modular code, testing, and version control
Hands-on experience with large datasets (millions of rows and beyond), including data that does not fit comfortably in memory
Practical understanding of performance: profiling code, identifying whether the bottleneck is CPU, memory, or I/O, and fixing it
Strong Python skills with pandas, NumPy, and numba
Strong SQL skills: complex joins, aggregations, window functions, indexing, and query optimization
Comfortable with Linux, Docker, cloud infrastructure, and CI/CD
Basic knowledge of statistics: descriptive statistics, probability, distributions, variance, correlation, sampling, and hypothesis testing basics
Machine learning knowledge: classic algorithms (linear and logistic regression, decision trees, random forests, gradient boosting, clustering), when and why to use each, cross-validation, and pitfalls such as overfitting and data leakage
Daily use of AI-assisted coding and research tools, with the habit of verifying what they produce
Ability to work independently and carry a problem from a vague question to a finished, verified result
Initiative and research ability: investigating unfamiliar problems, forming your own opinion, and proposing ideas

Nice to have

Deeper statistical methods (multiple-testing control, bootstrap, time-series statistics) and ML on noisy, low signal-to-noise data are a strong plus
Exposure to financial markets or crypto data, workflow tools (Airflow, Prefect, Dagster), and awareness of look-ahead and survivorship bias are a plus

We offer

Work at one of the first corporate-level algorithmic trading companies in Azerbaijan
Own the data layer of a real research and trading system from the ground up
Solve genuine performance problems at scale, where your optimizations are measured in hours saved every day
Have direct influence on research direction: your findings and proposals shape what we test next
Work closely with quantitative researchers and strategy developers in a small, fast-moving team within a fast-growing company
Grow professionally, with real opportunities for development and career progression
Private health insurance
Lunch, drinks, snacks, and fruit provided by the company
A centrally located office with modern amenities, including a game room and nap spaces
You’ll be working 5 days a week from 10 a.m. to 7 p.m. (13:00-14:00 lunch time)
Four days will be based in the office, and one day (Friday) you can work from home
Salary is competitive and negotiable based on experience and knowledge

Hiring process

Only shortlisted candidates will be invited to the further stages of the recruitment process