Description

Project: AI Portfolio Manager for Bonds

We need to develop an agent that will orchestrate several ML models to analyze bond order books and, based on this analysis, suggest optimal options for buying/selling securities to traders.

Responsibilities

• Communication with DE • Data collection and preparation (Hadoop, pyspark, writing parsers to collect external data) • Building models for tabular data • Anomaly detection in time series • Building time series prediction models • Generating trading signals based on unstructured data • Creating an RAG base for generating textual justifications for recommendations for traders • Testing various hypotheses

Requirements

· Education in the fields of "Mathematics", "Physics", "Mathematical Methods in Economics", (preferably graduates of Moscow State University, Moscow Institute of Physics and Technology, Higher School of Economics, and other leading universities in the country)

· Deep knowledge of probability theory and mathematical statistics

· Skills in writing high-quality Python code (knowledge of OOP, ability to write code optimized for speed and memory)

· Understanding of how ML model algorithms work (boosting, neural networks, NLP models, LLM)

· Proficiency in several Python libraries for classic ML from the list or relevant ones (numpy, sklearn, pandas, scikit-learn, matplotlib/seaborn/plotly, catboost/lightgbm/xgboost, fbprophet, pygam)

· Proficiency in pytorch or other DL frameworks

Conditions

• Comfortable modern office near Kutuzovskaya metro station
• Hybrid work format
• Corporate gym and relaxation areas
• Over 400 educational programs from SberUniversity for professional and career development
• Onboarding program and manager assistance at the start
• Referral bonus for recommending friends to the Sber team.