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Fincons Group

Global IT consulting and systems integration

Data Scientist Advanced

Applied Machine LearningPosted on Nov 10
Full-timeWarsaw, PolandNo salary listed

About the Job

Requirements

  • Has performed the role of Data Scientist in developing and deploying advanced analytics, artificial intelligence and machine learning solutions, including common data model design and end-to-end data science and machine learning solution delivery.
  • Expertise in advanced analytics, artificial intelligence, machine learning and data platform architecture, with a strong understanding of advanced analytical and AI-driven solutions.
  • Practical experience with Azure-based data science and AI services, including Azure Machine Learning, Azure AI Foundry and Azure OpenAI, covering experimentation, evaluation, deployment and lifecycle management.
  • Advanced practical experience in Python-based data science and machine learning development, sound knowledge of Python, R and SQL, and hands-on experience with pandas, scikit-learn, TensorFlow, PyTorch, MLflow and Spark/PySpark.
  • Expertise in data analytics and visualization, with hands-on experience in data visualization techniques and tools and in analyzing large volumes of structured, semi-structured and unstructured data.
  • Practical experience with data science and AI use cases including forecasting, predictive analytics, predictive maintenance, recommendation systems, classification, clustering, anomaly detection, natural language processing, document intelligence, information extraction, retrieval-augmented generation, video analytics and computer vision analytics.
  • Understanding of modern SQL, NoSQL and document databases, and experience with heterogeneous data sources such as APIs, enterprise platforms and large-scale datasets, with attention to data quality, lineage, metadata and reproducibility.
  • Familiarity with data engineering and data quality practices, and data science methodologies and processes including CRISP-DM, TDSP and KDD.
  • Practical experience with MLOps and DevOps practices, including version control, reproducible pipelines, model and artifact registries, CI/CD, automated testing, monitoring, documentation and controlled promotion between environments.
  • General knowledge of cloud and on-premises big data platforms, data mining and machine learning frameworks, and ability to design and operate AI workloads in hybrid cloud, on-premises and secure or restricted environments using technologies such as Docker and Kubernetes/OpenShift.
  • Strong understanding of AI ethics, responsible AI, model risk management, explainability, traceability, governance controls, data protection, bias mitigation and human oversight, together with awareness of market trends in advanced analytics and AI.
  • Ability to translate business needs into measurable data science requirements, propose realistic technical approaches, develop prototypes, communicate results and limitations to stakeholders, and produce clear documentation.
  • Excellent communication skills.
  • Ability to document effectively.
  • Problem-solving skills.
  • Leadership skills.
  • Practical knowledge of data science, machine learning model development and MLOps culture.
  • Analytical skills and understanding of the data scientist process.
  • Practical experience building and training machine learning and deep learning models.
  • At least two certifications among Certified Analytics Professional (CAP), CDP Data Engineer, CDP Data Analyst and Microsoft Certified Azure Data Scientist Associate.
  • English language proficiency at C1 level.
  • A Master’s degree and eight years of experience.

Responsibilities

  • Design and develop data analytics, data visualization and artificial intelligence solutions.
  • Elicit, analyze and translate business, user and technical requirements into data science specifications and user stories.
  • Support business experts and product owners during requirements definition, solution design and model development.
  • Maintain and manage requirements, user stories and data science artifacts throughout the solution lifecycle.
  • Produce technical documentation for data science models, analytical modules and related processes.
  • Define data science standards, estimate development effort and timelines, and contribute to quality assurance and change management activities.
  • Define, collect and monitor model performance metrics and business key performance indicators.
  • Manage model repositories, pipelines, testing and deployment activities, ensuring solution performance and accuracy.
  • Design, plan and manage prototypes and proof-of-concepts, and facilitate Design Thinking sessions with business stakeholders.
  • Manage and coordinate data science teams, contributing to project delivery and continuous improvement of data science and data engineering practices.

Desired Qualifications

  • Experience in data-driven organizations and Data & AI Centres of Excellence.

About the Company

Fincons Group

Global IT consulting and systems integration

Fincons Group provides IT consulting, system integration, and digital transformation services to help organizations manage technology changes. It delivers programs through a global delivery model, including the Bari Delivery Center and a Smart-Shore approach that blends nearshore Europe with offshore teams, and expanded to the US after acquiring PDG Consulting in 2024. It differentiates itself with four decades of organic growth under family leadership, deep client relationships, and deliberate international expansion built on technical skill. Its goal is to become a leading global IT consulting group by extending its geographic footprint and capabilities to help clients across industries implement technology-driven change.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Milan, Italy
Founded
1983

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