Data Scientist / Machine Learning Engineer at Xometry

, , Kazakhstan -

Full Time

Start Date

Immediate

Expiry Date

27 Jan, 26

Salary

0.0

Posted On

30 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Predictive Models, Forecasting, Python, SQL, AWS, MLOps, Data Engineering, Time-Series Analysis, Regression, Classification, Data Quality, Automation, Collaboration, Documentation

Industry

Software Development

Description

Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry’s digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity. About the Role We’re looking for a hands-on Data Scientist to take our analytics from reactive to proactive. You’ll design and deploy predictive and forecasting models that directly support business decision-making — starting small but aiming to lay the foundation for a future data science team. This is a builder role: you’ll own the full lifecycle from idea to production — data exploration, model development, validation, integration into dashboards or operational systems, and performance monitoring. You’ll work closely with analysts, engineers, and business stakeholders to turn predictions into action. What will you do: Build and maintain forecasting and predictive models for demand, supply, partner performance, and key operational KPIs. Build and refine the existing supplier claim/delay classification model and partner acceptance probability DNN, continuously improving accuracy and robustness. Clean, transform, and structure data from DWH and product systems; define features and maintain data quality. Automate model retraining, validation, and monitoring through backtesting, experimentation, and A/B testing. Collaborate with Data Engineering to deploy and automate model outputs into dashboards or operational workflows. Partner with analysts and stakeholders to identify and prioritize high-impact ML use cases across supply chain, fulfillment, and customer operations. Document models, maintain reproducibility, and drive continuous improvement of the ML lifecycle and tooling. Tech stack: Languages & Core libs: Python (pandas, NumPy, XGBoost, PyTorch or TensorFlow, statsmodels), SQL AWS & MLOps: SageMaker (training, processing, endpoints, pipelines), S3 Orchestration & CI/CD: Airflow, GitHub Actions (or similar), Docker Experiment tracking & registry: MLflow or SageMaker Model Registry; Data platform & Viz: Snowflake, Looker, Google Sheets Collab: JIRA, Confluence, Miro Examples of problem to be solved: Predict supplier claims or delays to enable proactive issue resolution and SLA management. Estimate partner acceptance probability for smarter order allocation and engagement optimization. Forecast customer-side lead times and costs to balance conversion rates with margin performance. Anticipate supply-demand imbalances and recommend corrective actions in planning or sourcing. Build early-warning systems for operational bottlenecks and performance risks. Experience: 3–5 years in Data Science, Machine Learning, or advanced analytics (preferably in forecasting, operations, or marketplace environments). Technical Skills: Strong proficiency in Python and SQL; experience with model development and validation using real-world data. Solid understanding of time-series analysis, regression, and classification methods. Familiarity with data pipelines, model deployment, and version control. Soft Skills: Strong analytical mindset, business acumen, and ability to communicate complex results clearly. Self-driven, curious, and comfortable working in a developing ML function with evolving tools and processes. Languages: English and Russian - fluent (must). German or another European language as a plus. Work conditions: Full-time job. Home office + long term contract Salary (fixed in Euros) to be discussed with each candidate. Significant bonuses Russian-speaking team of distributed data analysts with former employees from Yandex, Sber, Cian, Tinkoff, etc. in a large international company. Successful startup (400+ people in Europe) inside a global market leader (1500+ people overall). Team spirit and friendly atmosphere: we work in an open, friendly and trusting environment that welcomes initiative. In the Xometry team, everyone is ready to help and support in difficult times, and we always celebrate victories together and appreciate the contribution of everyone. Development opportunities: we are a fast growing company, each new task is an interesting challenge for the team. We care: ongoing free of charge well-being activities for our people, charity projects worldwide. Flexibility: speed and flexibility are some of our advantages, allowing us to achieve amazing results. We have flexible processes and planning, we can respond to rapidly changing conditions and remain effective in the face of uncertainty. Onboarding: Well structured onboarding plan for new employees combining all in one process, technology, and systems components. Please apply with an English CV #LI-Remote Xometry is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. Please read our privacy policy here.

Responsibilities

You will design and deploy predictive and forecasting models that directly support business decision-making. This role involves owning the full lifecycle from idea to production, including data exploration, model development, validation, and performance monitoring.