Technical Specialist - ML, Python

Job Summary

Currently, we are looking for a Data Scientist as we support our partner in developing a** Global Analytics Unit**—a global, centralized team with the ambition to strengthen data-driven decision-making and the development of smart data products for day-to-day operations. The team is designed to foster a data-driven entrepreneurial culture by acting as an incubator to turn ideas into action: creating smart data products across various business domains like sales, marketing, purchasing, logistics, and beyond.

The team has the autonomy to shape their approach, especially in terms of tools, technology, and introducing new concepts and solutions.

Data Scientist

We are searching for a Data Scientist to join our team of top-tier specialists, responsible for applying their expertise in machine learning,data mining, and information retrieval to design, prototype, and build next-generation analytics engines and services.

If you want to:

• Take part in developing and implementing complex smart data solutions.

• Work on bleeding-edge projects with a chance to see your visions come to life.

• Collaborate with world-class IT professionals.

• Work on projects addressing real business challenges in a global and diverse team.

• Have real impact on the projects and environment you work in.

• Propose innovative solutions and initiatives.

Moreover, if you like:

• Flexible working hours and a casual, non-corporate environment.

• Access to benefits such as Multisport, private medical care, and a modern office in the center of Warsaw with good transport links.

• Remote work options as much as you prefer.

• A relaxed atmosphere at work where your passion and commitment are appreciated.

• Vast opportunities for self-development through online courses, certifications, and global knowledge-sharing.

Then this role is certainly a good match!

Key Responsibilities

• Understanding business problems and designing smart data products.

• Developing complex models and algorithms to drive innovation within the organization.

• Conducting advanced statistical analysis to provide actionable insights, identify trends, and measure performance.

• Collaborating with data engineers to implement and deploy scalable solutions.

• Working closely with business teams to clarify ambiguous projects into concrete requirements.

• Designing and implementing time-series forecasting, anomaly detection, and demand-sensing solutions for business domains such as sales, marketing, pricing, supply chain, and logistics.

• Partnering with software and full-stack engineering teams to expose models through APIs, dashboards, and scalable user-facing applications that support day-to-day business decisions.

Skill Requirements

We Expect:

• MS or PhD in Computer Science, Statistics, Mathematics, Artificial Intelligence, Physics, or a related technical discipline.

• At least 5 years of experience in a statistical and/or data science role.

• Expertise in Python (experience with languages like R, MATLAB, Scala is a plus).

• 2+ years of hands-on Python ML Production experience (not just POC), with proficiency in deploying models to real-world systems.

• 3+ years of professional experience as a Data Scientist, with a focus on applying machine learning models to business problems.

• Strong software engineering skills, including unit testing,object-oriented programming, and familiarity with best practices like PEP8 and tools like Black.

• Familiarity with Azure Machine Learning (1+ year of experience) and building cloud-based ML solutions.

• Experience in Bayesian modeling (1+ year) and the application of probabilistic models.

• Fluency in the NumFOCUS stack: pandas, scikit-learn, Matplotlib, and Sci Py.

• Experience working with large datasets using tools like Spark and RDBMs.

• Experience with version control systems(e.g., Git) and knowledge of** DevOps tools** (Docker, Kubernetes, CI/CD pipelines).

• Proven ability to deploy models to production and plan products, considering the broader technical landscape.

• Professional attitude and service orientation.

• Team player with the ability to work autonomously on complex projects.

• Fluent English, as you will communicate primarily in English.

• Hands-on experience with time-series algorithms and forecasting methods such as ARIMA, SARIMA, SARIMAX, Exponential Smoothing, Prophet, VAR, and state-space models, along with modern machine learning and deep learning approaches such as XGBoost, LightGBM, LSTM, GRU, and Transformer-based forecasting.

• Strong understanding of time-series feature engineering, trend and seasonality decomposition, lag-based modeling, anomaly detection, model backtesting, and forecast evaluation using metrics such as MAE, RMSE, MAPE, sMAPE, and WAPE.

• Good full-stack engineering experience, including building and consuming REST APIs using FastAPI or Flask, integrating analytical services into microservice-based architectures, and collaborating on frontend applications built with frameworks such as React or Angular.

• Experience in delivering end-to-end data products with SQL/NoSQL databases, containerized deployments, cloud services, orchestration, observability, and secure production practices for business-facing analytical applications.

• Experience with Azure stack would be a plus.

Other Requirements

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