Senior Data Scientist
⚲ Warszawa, Śródmieście
20 000–36 000 zł / mies. (zal. od umowy)
Wymagania
- Python
- NumPy
- pandas
- SciPy
- scikit-learn
- Matplotlib
- Git
- Tensorflow
- PyTorch
- JAX
- PyMC
- Stan
- NumPyro
Opis stanowiska
Nasze wymagania:
Solid, hands-on experience in Data Science, Machine Learning, or quantitative research (a plus if it includes finance, time-series modeling, stochastic calculus or decision-making under uncertainty).
Working knowledge of current ML methods, and the ability to read research papers and turn them into working implementations.
A solid grasp of probability theory and statistics - distributions, estimation, Bayesian inference, hypothesis testing - and of the mathematical/statistical foundations of ML algorithms (optimization, regularization, attention mechanisms, encoder-decoder architectures).
Strong Python skills, with practical experience in core numerical, statistical, and visualization libraries (NumPy, pandas, SciPy, scikit-learn, Matplotlib), optionally ML frameworks (Tensorflow, PyTorch, JAX).
Ability to design, implement, and validate probabilistic or forecasting models using methods such as quantile regression, GARCH-type models, and Monte Carlo simulation.
Ability to write clean, testable, well-documented code and to work comfortably with Git.
Ability to work independently and take initiative in deciding the next steps of a project.
Genuine interest in understanding financial markets and investment instruments, and in applying Data Science or ML knowledge to real-world problems.
Willingness to adapt existing ML methods, or develop new ones, to meet the specific challenges of the finance industry.
We require proficiency in both Polish and English, spoken and written, at a minimum B2 level.
Mile widziane:
Experience with optimization methods (e.g., genetic/evolutionary optimization).
Hands-on experience with probabilistic programming (PyMC, Stan, NumPyro).
Basic knowledge of how financial markets and financial instruments work.
Experience running computations on compute clusters or remote servers.
Research publications or independent projects in quantitative finance.
Experience working with AI-assisted research/coding tools (agentic coding assistants).
O projekcie:
Join the data science team at AI Investments. We use advanced mathematical models, statistics, and machine learning to make investment decisions. As part of this role, you will also take on a quantitative-research focus: developing methodology to forecast the probability distribution for future financial events and turning that methodology into tested, production-quality code. If you are passionate about data analysis, have a deep understanding of statistics, ML algorithms, and maybe even stochastic calculus, and are ready for the challenges of the financial industry, we encourage you to apply.
The ideal candidate is an experienced data science, machine learning or quantitative finances specialist with a strong commercial or academic track record and a research-driven mindset. You should be comfortable applying the scientific method in practice: formulating hypotheses, designing experiments, critically evaluating results, and drawing well-supported conclusions. Because many of the problems we address have no ready-made solutions, this role requires intellectual independence, unconventional thinking, and the initiative to explore both the technical and financial dimensions of a challenge. We are looking for someone who goes beyond implementing models - someone who can conduct rigorous research, take ownership of complex questions, and develop innovative approaches that can meaningfully influence investment decisions.
Zakres obowiązków:
Design and implement mathematical, statistical and machine learning models that forecast the probability for future financial events.
Conduct data analyses that support investment decisions.
Build and implement statistical and Bayesian models - e.g., GARCH-type volatility models, quantile regression, conditional-distribution models, and Monte Carlo methods.
Carry out in-depth analysis of ML algorithms with respect to their effectiveness and limitations.
Backtest and validate models; assess forecast quality through calibration checks, statistical tests, and error metrics.
Optimize existing models for speed, accuracy, and scalability.
Write clean, well-documented Python code.
Prepare concise research documentation - assumptions, formula derivations, conclusions - that is easy to follow for a STEM-educated reader, and present findings internally.
Collaborate with the investment team to identify and solve analytical problems, and set your own goals and priorities within projects.
Oferujemy:
Work in an experienced team, with direct exposure to leading experts in machine learning and investing.
Opportunities to grow your expertise and present research at scientific and industry conferences, mentoring and technical guidance from experienced leaders in respective fields.
Creative, research-driven work with a high degree of autonomy over your research process and direction.
Attractive compensation with a performance-linked bonus system.
A friendly work environment, reflected in very low staff turnover.
Hybrid work (1 day in the office, 4 remote) and flexible working hours.
Solid, hands-on experience in Data Science, Machine Learning, or quantitative research (a plus if it includes finance, time-series modeling, stochastic calculus or decision-making under uncertainty).
Working knowledge of current ML methods, and the ability to read research papers and turn them into working implementations.
A solid grasp of probability theory and statistics - distributions, estimation, Bayesian inference, hypothesis testing - and of the mathematical/statistical foundations of ML algorithms (optimization, regularization, attention mechanisms, encoder-decoder architectures).
Strong Python skills, with practical experience in core numerical, statistical, and visualization libraries (NumPy, pandas, SciPy, scikit-learn, Matplotlib), optionally ML frameworks (Tensorflow, PyTorch, JAX).
Ability to design, implement, and validate probabilistic or forecasting models using methods such as quantile regression, GARCH-type models, and Monte Carlo simulation.
Ability to write clean, testable, well-documented code and to work comfortably with Git.
Ability to work independently and take initiative in deciding the next steps of a project.
Genuine interest in understanding financial markets and investment instruments, and in applying Data Science or ML knowledge to real-world problems.
Willingness to adapt existing ML methods, or develop new ones, to meet the specific challenges of the finance industry.
We require proficiency in both Polish and English, spoken and written, at a minimum B2 level.
Mile widziane:
Experience with optimization methods (e.g., genetic/evolutionary optimization).
Hands-on experience with probabilistic programming (PyMC, Stan, NumPyro).
Basic knowledge of how financial markets and financial instruments work.
Experience running computations on compute clusters or remote servers.
Research publications or independent projects in quantitative finance.
Experience working with AI-assisted research/coding tools (agentic coding assistants).
O projekcie:
Join the data science team at AI Investments. We use advanced mathematical models, statistics, and machine learning to make investment decisions. As part of this role, you will also take on a quantitative-research focus: developing methodology to forecast the probability distribution for future financial events and turning that methodology into tested, production-quality code. If you are passionate about data analysis, have a deep understanding of statistics, ML algorithms, and maybe even stochastic calculus, and are ready for the challenges of the financial industry, we encourage you to apply.
The ideal candidate is an experienced data science, machine learning or quantitative finances specialist with a strong commercial or academic track record and a research-driven mindset. You should be comfortable applying the scientific method in practice: formulating hypotheses, designing experiments, critically evaluating results, and drawing well-supported conclusions. Because many of the problems we address have no ready-made solutions, this role requires intellectual independence, unconventional thinking, and the initiative to explore both the technical and financial dimensions of a challenge. We are looking for someone who goes beyond implementing models - someone who can conduct rigorous research, take ownership of complex questions, and develop innovative approaches that can meaningfully influence investment decisions.
Zakres obowiązków:
Design and implement mathematical, statistical and machine learning models that forecast the probability for future financial events.
Conduct data analyses that support investment decisions.
Build and implement statistical and Bayesian models - e.g., GARCH-type volatility models, quantile regression, conditional-distribution models, and Monte Carlo methods.
Carry out in-depth analysis of ML algorithms with respect to their effectiveness and limitations.
Backtest and validate models; assess forecast quality through calibration checks, statistical tests, and error metrics.
Optimize existing models for speed, accuracy, and scalability.
Write clean, well-documented Python code.
Prepare concise research documentation - assumptions, formula derivations, conclusions - that is easy to follow for a STEM-educated reader, and present findings internally.
Collaborate with the investment team to identify and solve analytical problems, and set your own goals and priorities within projects.
Oferujemy:
Work in an experienced team, with direct exposure to leading experts in machine learning and investing.
Opportunities to grow your expertise and present research at scientific and industry conferences, mentoring and technical guidance from experienced leaders in respective fields.
Creative, research-driven work with a high degree of autonomy over your research process and direction.
Attractive compensation with a performance-linked bonus system.
A friendly work environment, reflected in very low staff turnover.
Hybrid work (1 day in the office, 4 remote) and flexible working hours.
🔍 Dekoder Ogłoszenia
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Solid, hands-on experience in Data Science, Machine Learning, or quantitative research (a plus if it includes finance, time-series modeling, stochastic calculus or decision-making under uncertainty).
Oczekują od Ciebie nie tylko teoretycznej wiedzy, ale przede wszystkim praktycznego doświadczenia w tworzeniu i wdrażaniu modeli, a dodatkowe specjalizacje są mocno preferowane.
🔴
the ability to read research papers and turn them into working implementations.
Musisz być w stanie samodzielnie zrozumieć nowe algorytmy z publikacji naukowych i przekształcić je w działający kod.
🔴
Ability to work independently and take initiative in deciding the next steps of a project.
Oczekują, że będziesz samodzielnie zarządzać swoją pracą i podejmować kluczowe decyzje projektowe bez ciągłego nadzoru.
🔴
Genuine interest in understanding financial markets and investment instruments, and in applying Data Science or ML knowledge to real-world problems.
Oczekują, że będziesz pasjonatem finansów i będziesz aktywnie szukać zastosowań dla swojej wiedzy w tej dziedzinie, a nie tylko wykonywać zadania.
🔴
Willingness to adapt existing ML methods, or develop new ones, to meet the specific challenges of the finance industry.
Nie wystarczy stosować gotowe rozwiązania; musisz być gotów modyfikować istniejące lub tworzyć nowe algorytmy specjalnie dla potrzeb sektora finansowego.