Data Engineer at SGS Digicomply ZLÍN

SGS DIGICOMPLY is a digital platform that delivers compliance intelligence to brand owners, traders, and manufacturers in the food industry. Part of SGS SA - the world's leading inspection, verification, testing, and certification company - we are on a mission to push the boundaries of AI and data analytics to solve problems aimed at giving safer, sustainable, and compliant products to consumers. We aim to maximize the positive and transformative impact of the latest technologies on the food and CPG industry.

As SGS Digicomply’s Data Engineer, you will collect, analyze, and interpret large data sets, which are used to develop data-driven solutions to difficult business challenges. You will work on your own, as well as in collaboration with the development team or regulatory specialists team. Your expertise will be vital to managerial decisions on product development.

Main Responsibilities:

• Extract data from primary or secondary data sources.
• Filter, clean, and standardize data extracted to build an accurate data set to allow effective data analysis.
• Interpret data, analyze results, perform data mining using comparative analytics, data matching, and statistical techniques, and provide ongoing reports and visualization tools.
• Identify, analyze, and interpret trends or patterns in complex data sets.
• Develop and implement quality control processes to ensure data integrity and accuracy throughout the data manipulation process.
• Collect laws, regulations, orders, and other legislative texts related to the food industry.
• Organize the texts identified in collections.
• Work closely with management to prioritize business and information needs.
• Interact with clients.

Skills and Knowledge:

• Strong data mining and analytical skills.
• Strong problem-solving skills with an emphasis on product development.
• Proficiency in statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Ontology knowledge.

General Requirements:

• At least 2 years of experience manipulating data sets and building statistical models.
• Experience in food analytical laboratories (familiarity with LIMS).
• Degree in Statistics, Mathematics, Computer Science, or another quantitative field.
• Understanding of multiple analytical functions.
• Problem-solving and data storytelling skills.
• Proactive, innovative, and collaborative person.
• Self-driven, highly motivated, and detail-oriented.
• Great team player.
• English: B2-C1.

We Offer:

• Employment or remote job.
• An interesting and challenging job with space for your growth.
• An international and highly motivated team.
• Benefits including pension insurance, benefit card, meal vouchers.
• 2 sick days, 2 flex days, 21 days vacation plus every year + 1 day up to 26 days.