Senior Data Scientist

U. S. Steel Košice is the largest integrated steel producer in Central Europe delivering steel to customers in industries such as automotive, home appliance manufacturing, construction.

U. S. Steel Košice will welcome a Data Scientist in its ranks to develop scalable Python-based applications that will improve process efficiencies and plant operations in line with the overarching strategic and tactical objectives of the company.

As a Data Scientist in U. S. Steel, you will collaborate with internal business partners to implement data-driven solutions with measurable business value. You will work with other data scientists, software developers and project managers on multiple projects, using mathematics, statistics, and machine learning to retrieve structure and knowledge from raw data. You will work at a cross section of machine learning and analytic processes to develop solutions that will improve efficiency and drive revenue.

Duties and responsibilities

• Build statistical models for data analysis of manufacturing processes by facilitating automation, performing parameter optimization and machine learning model re-training, including a setup and maintenance of back-end infrastructure to facilitate its ongoing operation on-premises (and potentially on the cloud in the future).
• Develop and deploy predictive and prescriptive analytic solutions in Python.
• Develop analytics to address customer needs and opportunities.
• Process, clean, and verify the integrity of the data used for analysis.
• Enhance data collection procedures to include information that is relevant for building analytic systems.
• Perform rapid ad-hoc analysis and present results in a clear manner starting with structured or unstructured datasets.
• Keep up to date with latest technology trends.

Qualifications

• University degree in Computer Science, Information Systems or related discipline (including Statistics, Data Science, Mathematics, Engineering) with 2-3 years of prior equivalent work experience in data analysis instead of an advanced degree.
• Proficiency in designing, conducting, and interpreting statistical analyses using common statistical software tools (e.g., R, Python, etc.) and techniques (e.g., regression modeling, survival analysis, machine learning, etc.) with proven / demonstrable experience.
• Expertise in leveraging statistics, machine learning algorithms, and advanced mathematics to solve engineering problems.
• Demonstrated skill in the use of one or more analytic, visualization, and data querying software tools or languages.
• Demonstrated skill in data cleansing, data quality assessment, data visualization and storytelling for stakeholders.
• Understanding relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.

Nice to-have

• Experience with big-data analysis built upon structured (SQL) and unstructured (data lakes) file systems will be a plus.
• Industry experience is desirable, but not essential.