Data Scientist - Deep Learning Forecasting

Fetcherr

Poland · Full-time · Not Applicable

Data Scientist - Deep Learning Based Demand Forecasting

Fetcherr is an AI-driven company specializing in deep learning, algorithmic trading, and large-scale data solutions. Our core technology, the Large Market Model (LMM), enables accurate demand forecasting and real-time, data-driven decision-making. Originally focused on the airline industry, Fetcherr is expanding its AI solutions across additional industries.

We are seeking a talented and self-driven experienced Data Scientist to help advance our machine learning capabilities.This is a key role for someone passionate about leveraging machine learning to solve complex, real-world problems and deliver measurable business impact.

Responsibilities:

Develop and implement state-of-the-art econometric and machine learning models for demand forecasting.
Conduct research and experimentation to evaluate novel approaches for improving accuracy, robustness, and scalability.
Collaborate with cross-functional teams (including product, data engineering, and backend) to deploy ML systems in production.
Mentor junior team members and promote best practices across modeling, experimentation, and code quality.
Clearly communicate complex technical findings to non-technical stakeholders, including product leaders and executives.

Requirements:

You’ll be a great fit if you have...

5+ years of hands-on experience in data science and machine learning with a proven record of leveraging modeling into business outcomes.
Proficiency in Python and its ML/data stack (e.g., PyTorch or TensorFlow, Pandas, NumPy, Scikit-learn, SQL).
Expertise in time-series forecasting, ideally Deep Learning based, preferably in demand prediction or related areas.
Domain expertise in revenue management related pipelines, domains, problems.
Feature engineering, feature importance testing, per sample explainability based experience.
Master’s or PhD in Computer Science, Machine Learning, Statistics, Engineering or a relevant field.
Publications in top-tier, peer-reviewed ML/AI venues (e.g. ICLR, ICML, NIPS, etc.)
Solid understanding of ML production workflows (versioning, testing, reproducibility, and deployment).
Excellent communication and collaboration skills.

Nice to have:

Experience applying ML in domains like finance, trading, reinforcement learning, or NLP.
Familiarity with cloud based solutions on GCP platform (e.g., Vertex AI, PubSub, Cloud Run Functions).
Strong data visualization and exploratory data analysis skills.
Familiarity with code optimization, containerization (e.g., Docker), CI/CD, or cloud-native architectures.
Participation in competitive programming or data science challenges (e.g., Kaggle).

If you're excited about building impactful AI systems in a high-growth startup environment, and want to help redefine how industries price, forecast, and optimize, we’d love to hear from you.

Key Skills

Ranked by relevance

machine learning ai deep learning cloud data visualization containerization data analysis tensorflow pytorch python docker pandas numpy cicd gcp

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