Data Science Engineer

Key Skills

Java Programming, Finance, Python Programming, SQL, Jupyter Notebook, R-Shiny

Job Description

We are hiring for this job offer in Krakow, Katowice, Gdansk.

What will you do with us?

• You will integrate and process data for Data Science projects,
• you will design and optimize statistical models and AI/ML algorithms,
• you will cooperate with the Client and SMEs to refine expectations and get clarity on expected results of data analysis’,
• you will cooperate with data analysts, data engineers, business analysts as well as Data Science solutions architects,
• you will scale algorithms for implementation in Big Data environments.

We are looking for you if:

• you have at least 2-years of commercial experience in Data Science projects in the field of building models to process and analyze data in various business areas (finance, HR, production or other),
• you have experience using programming tools such as: Python (alternatively IPython, Jupiter Notebooks) or R (alternatively R Shiny),
• you are familiar with mathematical and statistical models as well as algorithms used in Data Science for example: deep learning, neural networks, linear/logistic regression, decision trees, random forest,
• you have an IT, Mathematics or other?science degree?of higher education,
• you communicate?well?in English.

In return, you will receive from us:

• individual development plan to support your competencies’ growth,
• rich offer of professional trainings and language courses,
• extra benefits: social benefit package, including private medical care package to choose, insurance package, Multisport card and sponsored sports activities and a lot more,
• possibility of car leasing on preferential conditions – Master Benefit,
• possibility of using increased tax deductible costs in the case of creative work,
• flexible working hours,
• support for relocation,
• free parking spaces and closed bicycle boxes,
• online access to over 2000 audiobooks and podcasts,
• permanent employment contract from the first day at work.