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Chief Business Intelligence Architect

2 tygodni temu

Wrocław, Polska FIEGE Sp. z.o.o. Pełny etat
Job Description

We are FIEGE Sp. z.o.o., a family-owned company leading innovations in logistics, digital, real estate, and ventures for over 150 years.

We seek an experienced Chief Business Intelligence Architect to join our growing Data & AI team. Our mission is to enhance warehouse operations and customer processes through AI, creating significant value quickly and collaboratively. You will work closely with warehouse locations and customers to develop innovative AI solutions and drive our transformation into a data-driven company. If you are passionate about data and AI and thrive in a dynamic, innovative environment, we want to hear from you.

Key Responsibilities:
  • Model Development and Implementation: Develop and optimize machine learning models (e.g., regression, classification, clustering, time series, recommendation systems) or deep learning to improve business and logistics processes.
  • Data Analysis and Preparation: Analyze complex datasets from various sources (e.g., warehouse management systems, transport management systems) as well as feature engineering and exploratory data analyses to identify optimization potentials.
  • Evaluation and Testing: Conduct and evaluate A/B tests to validate models, regularly evaluate ML applications.
  • Product Development: Develop AI products from conception to rollout.
  • Collaboration and Stakeholder Management: Work closely with various stakeholders and customers to identify and implement use cases.
  • Best Practices and Mentoring: Promote best practices within the team and mentor junior data scientists.
Required Skills and Qualifications

Academic Qualification: Degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.

Professional Experience: At least 7 years of experience as a data scientist, including 1-2 years in model operationalization (MLOps). Experience in data engineering and software development is a plus.

Technical Knowledge:

  • Solid programming skills in Python (e.g., PySpark, Pandas, Scikit-Learn, TensorFlow, PyTorch, etc.) and SQL.
  • Knowledge in data visualization and data preparation (e.g., sampling methods).
  • Experience with cloud environments (Microsoft Azure, Azure Synapse, and Databricks).
  • Model implementation: Experience in deploying and optimizing machine learning models in production environments, preferably in Databricks.
  • DevOps skills: Experience in DevOps for machine learning (MLOps).
  • Software Development Fundamentals: e.g. containerization, versioning/GIT, working with CI/CD pipelines.
  • Tech Stack: Ability to make informed decisions about the tech stack.
  • Deep Learning: Knowledge of neural networks and prompt engineering techniques is an advantage.
  • Logistics Processes: Knowledge of logistics is an advantage to better understand the specific requirements and challenges of the industry.
  • Analytical Skills: Strong analytical thinking and problem-solving skills, with the ability to convey complex technical issues clearly.
  • Communication Skills: Ability to define use cases and present content in an understandable way for non-experts; experience in direct customer contact is an advantage.
  • Teamwork: Experience with agile working methods and the desire to develop further in an agile team.
  • Language Skills: Fluent in English, both written and spoken.