DATA SCIENTIST

Teka Systems Open

Marousi Mid-level Data Science

At a glance

Mid-level Data Science role at Teka Systems. Marousi.

Pay not stated Data Scientist salary

RoleData Science

SeniorityMid-level

LocationMarousi

PostedOct 1, 2026

Role brief

dataroles summary, based on the employer's posting.

What you'll do

Turn business questions into analytical use cases with stakeholders and domain specialists
Explore data from varied sources to find patterns, anomalies, trends, and business opportunities
Build and assess statistical or machine-learning models, choosing methods that suit each problem
Explain model results, assumptions, and recommendations to technical and non-technical audiences
Work with data engineering and IT teams on deployment and monitoring of analytical solutions

What you bring

A relevant quantitative degree, such as data science, mathematics, engineering, or another listed discipline
Two to four years in data science, advanced analytics, machine learning, or a related quantitative area
Practical Python and SQL skills, plus knowledge of statistics, feature engineering, model validation, and performance measures
Experience applying machine-learning methods to business problems and communicating findings to stakeholders
Written and spoken English proficiency

Who this fits

This role suits a mid-level data scientist who wants hands-on work spanning analysis, machine learning, and collaboration with business and technical teams. You’ll contribute as part of an analytics team, working across corporate and industrial areas.

From the employer

STEELMET S.A. is searching for its headquarters a Data Scientist

Steelmet offers corporate services such as: Strategic Development, International Business Operation, Sustainability, Non-ferrous Metal Purchasing, Resource Recovery & Central Procurement, Supply Chain & Logistics, Operational Excellence, IT, Information Security, HR, Communication, Financial and Auditing Services to the Viohalco Companies aiming to support them and drive best practices across the business segments.

We are looking for a Data Scientist to join the Advanced Analytics & Data Science team and help turn business questions into practical, data-driven solutions across corporate and industrial areas.

The role combines hands-on analytics, machine learning, and stakeholder collaboration. The successful candidate will work with business teams, domain experts, Data Engineers, and technology teams to understand real business needs, build robust analytical models, and communicate insights in a clear and actionable way.

Key Responsibilities

- Partner with business stakeholders and domain experts to frame business challenges as clear analytical use cases.
- Prepare, explore, and analyze structured and unstructured data from different sources.
- Perform exploratory data analysis to identify patterns, trends, anomalies, and business opportunities.
- Build, test, and validate statistical and machine learning models suitable for the problem at hand.
- Use methods such as regression, classification, clustering, forecasting, anomaly detection, recommendation, and optimization where relevant.
- Evaluate model performance using appropriate technical and business metrics.
- Explain findings, assumptions, limitations, and recommendations clearly to both technical and non-technical audiences.
- Write clean, maintainable, documented analytical code that can be reused and reviewed by others.
- Work with Data Engineering and IT colleagues to support deployment, monitoring, and ongoing improvement of analytical solutions.
- Contribute to analytics and AI initiatives, including machine learning and selected Generative AI use cases where appropriate
- Follow applicable data governance, information security, quality, and Responsible AI standards.
- Contribute to knowledge sharing and Data Science best practices within AA&DS.

Required Qualifications

- Bachelor’s (or Master’s degree) in Data Science, Computer Science, Physics, Mathematics, Engineering, Statistics, or another relevant quantitative discipline.
- 2 to 4 years of professional experience in Data Science, Advanced Analytics, Machine Learning, or a related quantitative field.
- Experience applying data science and machine learning methods to real business problems.
- Strong proficiency in Python and SQL.
- Solid understanding of statistics, machine learning, feature engineering, model validation, and performance evaluation.
- Practical experience with common Data Science libraries and frameworks, such as pandas, NumPy, scikit-learn, XGBoost, or LightGBM.
- Experience with deep learning techniques (neural networks, CNNs)
- Experience creating data visualizations and communicating analytical findings to stakeholders.
- Familiarity with Git or another version-control system.
- Good command of written and spoken English.

Preferred Qualifications

- Experience with Microsoft Azure, Databricks, or another cloud-based analytics platform.
- Experience with Power BI, Grafana or a similar data visualization platform.
- Exposure to deep learning frameworks such as TensorFlow, Keras, or PyTorch.
- Exposure to Generative AI, large language models, Retrieval-Augmented Generation (RAG), or agent-based AI solutions.
- Experience with forecasting, mathematical optimization, anomaly detection, recommendation systems, or computer vision.
- Familiarity with model deployment, monitoring, and MLOps practices.
- Experience in manufacturing, industrial operations, supply chain, procurement, commercial, finance, energy, or sustainability analytics.