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Machine LearningItransition Group • United States
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Machine Learning

Itransition Group
  • US
    United States
  • US
    United States
Jetzt Bewerben

Über

We are looking for a Machine Learning Researcher to design, develop, and evaluate predictive models for financial markets. You will work at the intersection of quantitative research, machine learning, and real-world trading constraints, contributing to alpha generation and risk modeling. office remote Poland Requirements
3+ years of relevant experience Strong Python skills and experience with ML ecosystems (AWS Sagemaker, MLFlow) Hands‑on experience working with tabular/time series data with usage of ML Solid understanding of machine learning fundamentals: Supervised learning, feature engineering, model evaluation; Overfitting, regularization, cross‑validation Knowledge of statistical methods and probability theory Experience with experiment design and offline evaluation Ability to work with large datasets and build efficient data processing pipelines Familiarity with SQL and data querying Strong analytical and problem‑solving mindset Ability to clearly communicate findings and trade‑offs Ownership of tasks from research to implementation Curiosity and willingness to explore new approaches Level of English enough for efficient technical and business communication with native speakers
Nice to have
Experience in financial machine learning, quantitative finance, or trading systems knowledge of signal generation, alpha research, portfolio construction or risk modeling Experience with: Deep learning for tabular/time series data (Transformers, RNNs, etc.); Probabilistic modeling or Bayesian methods Hands‑on experience with production ML systems (MLOps, monitoring, retraining) Ability to define research direction and identify high‑impact opportunities Ability to translate business problems into ML solutions
Responsibilities
Develop and validate machine learning models for financial time series and cross‑sectional data Conduct research on alpha signals, feature engineering, and predictive modelling techniques Design experiments and backtesting frameworks with proper statistical rigor Work with large‑scale structured and unstructured financial datasets Collaborate with engineering teams to deploy models into production pipelines Analyze model performance, stability, and robustness under changing market conditions Improve data pipelines, labeling strategies, and evaluation methodologies
We offer
Projects for such clients as PayPal, Wargaming, Xerox, Philips, Adidas and Toyota Competitive compensation that depends on your qualification and skills Career development system with clear skill qualifications Flexible working hours aligned to your schedule #J-18808-Ljbffr
  • United States

Sprachkenntnisse

  • English
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