Data Scientist

POSITION TITLE: Data Scientist

Key Purpose Statement - Core mission

The key purpose or core mission of the Data Scientist position is to drive Data science in FEG business and build statistical and ML based models, and insights.

RESPONSIBILITIES

• Retrieve the data from different data sources i.e., Data Lake and Data Ware House using SQL, Python or PySpark
• Cleaning and preprocess the data for quality and accuracy
• Perform EDA to identify patterns, trends and insights using statistical methods
• Develop and implement machine learning models for customer behavior, revenues, campaigns
• Enhance the existing models by adding more features and expand it to other markets / teams
• Working with other teams such as engineering, product development, and marketing to understand their data needs and provide actionable insights
• Support the data analytics team in improving analytical models with data science-based insights
• Develop and provide MLOps framework on Microsoft Azure for deploying ML models (good to have)

REQUIREMENTS - KNOWLEDGE, SKILLS AND EXPERIENCE

Education (High/University), language knowledge (level of EN, CZ, .. ), length of practice and experiences required:

• A degree in Computer Science / Information Technology
• Fluent communication skills in English both written and verbal
• Team player who can share experience with the team and grow them technically
• High quantitative and cognitive ability to solve complex problem and think with a vision

Qualifications, knowledge of XY , specific technology; hard and soft skills required:

• At least 4 years of experience of working in data roles - Data Analyst, Business Analyst and Data Scientist
• 3 + years of experience in programming and data science, MLOps and automation of models
• Sound practical knowledge of working with advanced statistical algorithms
• Great understanding of all machine learning techniques and its application on business problems
• Experience with ML on MS Azure stack in combination with Python, SQL
• Strong business understanding. Worked in developing analytics solutions in 2-3 Domains
• Experience in building and productionizing ML platforms.