Quantitative Developer for Alternative Data Team

We are seeking a Quantitative Developer with mathematical background, strong programming skills (Python) and understanding of ML/DL algorithms who will be responsible for building
trading strategies in fixed income and equities Markets.

Our Tech stack:

Python (pandas, scipy, torch, tensorflow… + specific quantitative libraries (QuantLib…));
PostgreSQL, Greenplum, ClickHouse + Airflow + RabbitMQ / Kafka;
Gitlab CI/CD, Docker, Kubernetes.

Responsibilities:

Find and check new hypothesis based on market data and trends in finance area with the purpose to improve current models and create new ones;
Analyse and back test developed strategies;
Provide strategy performance analysis;
Apply machine learning (DL, RL…) algorithms for trading strategies. Construct complex reproducible ML pipelines (based on KubeFlow);

Work closely with Research and DevOps teams.

Requirements:

2+ years’ experience as a Quantitative Researcher / Data scientist on financial markets;
BSc, MSc or PhD in computer science, mathematics, statistics, physics, economics or finance;
Excellent knowledge of Python and proficiency in pandas, scipy, pytorch;
Very good knowledge of SQL;
Knowledge of Git;
Experience in Docker, Kubernetes;

Excellent background in Statistics/Probability Theory. Experience in building advanced statistical/probability models;
Financial knowledge (asset pricing, financial econometrics, derivatives, market microstructure). Deep understanding of fin. instruments including but not limited to bonds, FX/IR swaps and their pricing;
Machine learning: experience in robust ML/DL models implementation;
Understanding of algorithms and data structures.

What we offer:

Possibility to work remotely;
Low formalism/ bureaucracy corporate culture;
Opportunity to drive projects with direct PnL impact;
Excellent social package.

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