Machine Learning

Itransition Group; Town of Poland (NY); On-site; USD 100,000 - 140,000; Full time

Benefits offered by this job

Competitive compensation

Career development system

Flexible working hours

Job summary

A leading technology firm is seeking a Machine Learning Researcher to design and evaluate predictive models for financial markets. The ideal candidate will have over 3 years of experience and strong skills in Python and machine learning ecosystems like AWS Sagemaker. Key responsibilities include developing ML models, conducting research on alpha signals, and collaborating with engineering teams. Competitive compensation and flexible working hours are offered for this role located in New York.

Qualifications

• 3+ years of relevant experience in machine learning.
• Ability to work with large datasets and build data processing pipelines.
• Experience in financial machine learning is a plus.

Responsibilities

• Develop and validate machine learning models for financial time series data.
• Conduct research on alpha signals and predictive modeling techniques.
• Collaborate with engineering teams to deploy models.

Skills

Strong Python skills

Experience with ML ecosystems (AWS Sagemaker, MLFlow)

Hands-on experience with tabular/time series data

Solid understanding of machine learning fundamentals

Knowledge of statistical methods and probability theory

Strong analytical and problem-solving mindset

Familiarity with SQL

Effective communication skills in English

Job description

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