Associate Data Scientist
Who we are
The next step of your career starts here, where you can bring your own unique mix of skills and perspectives to a fast-growing team.
Metyis is a global and forward-thinking firm operating across a wide range of industries, developing and delivering AI & Data, Digital Commerce, Marketing & Design solutions and Advisory services. At Metyis, our long-term partnership model brings long-lasting impact and growth to our business partners and clients through extensive execution capabilities
With our team, you can experience a collaborative environment with highly skilled multidisciplinary experts, where everyone has room to build bigger and bolder ideas. Being part of Metyis means you can speak your mind and be creative with your knowledge. Imagine the things you can achieve with a team that encourages you to be the best version of yourself.
We are Metyis. Partners for Impact.
What we offer
Enjoy a high level of responsibility and immediate client interactions under the guidance of senior team members.
Interact with data team on regular basis to drive innovation and create impact on our clients
Help our clients to target, measure and improve mission-critical business metrics and generate demonstrable return on investment.
Become part of a fast-growing international and diverse team
What you will do
Metyis is growing! We are looking for a data professional to join our Data Science team.
Own live forecasting and optimization models, keeping them accurate and adapting them as constraints and business rules change.
Scope and develop new data science projects end to end, from problem framing to deployment.
Apply machine learning and generative AI to extend solutions where they add value.
Answer client business questions using data & scenario analyses and provide clear recommendations.
Present results to client stakeholders, including senior management.
Work with data and engineering teams on data quality, deployment and cloud performance.
Guide junior colleagues and review their work.
What you will bring
3–6 years of professional experience in data science or advanced analytics, delivering projects for business stakeholders.
Business acumen: you can connect data science model outputs and data analysis to business processes (related to functions such as cost, service, inventory, delivery etc.) and communicate insights & recommendations clearly to business stakeholders in English.
Strong Python (pandas, scikit-learn), SQL and Git; you can debug and improve someone else's code.
Optimization: a solid grasp of optimization concepts, such as objectives, constraints and trade-offs, and experience configuring optimization tools and interpreting their results.
Supply chain: working knowledge of demand forecasting, inventory and replenishment, and KPIs such as forecast accuracy and service level.
Cloud: experience running data and ML workloads on Azure, AWS or GCP, ideally with Databricks or Spark.
Machine learning: hands-on experience building and deploying models, such as gradient boosting and time series forecasting, with scikit-learn, XGBoost or LightGBM, including evaluation and drift monitoring.
Generative AI: practical exposure to generative AI and a good sense of where it can add value to business processes.
A degree in a quantitative field, such as engineering, statistics, computer science or operations research.
Nice to have
MLOps tooling, such as MLflow, Docker and CI/CD.
Orchestration tools, such as Airflow or Azure Data Factory.
Experience with logistics, pricing or S&OP analytics.
Consulting or other client-facing experience.
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