Data Scientist (R-15968)
Solna - Sweden
Data & Analytics /
Employee: Part Time /
Hybrid
You will be part of our B2C Sales & Marketing Services Analytics team. We are a team of data scientists and analysts, working across the Nordics to create, promote and grow our B2C offering. Our success relies on collaboration – both within the team, and with other teams such as Product, Data, Tech and Sales teams.
Job description
- Analyze large datasets with different types of data from Dun & Bradstreet's sources as well as several different types of customer data.
- Develop models and new attribute variables, and deliver on client specific projects (targeting optimization, segmentations etc)
- Apply machine learning techniques to build predictive models and other data driven solutions.
- Evaluate model performance using appropriate metrics and validate models to ensure reliability and robustness.
- Join cross-team collaboration to develop Analytics capabilities integrated in our products
- Contribute with your expertise on new data sources and internal product development processes.
- Thirst for advancements in data science and machine learning to enhance expertise and contribute to innovation.
We are looking for a Data Scientist sharing our values
- You like working in teams
- You are a social person who likes to share your expertise, experiences and tips.
- You are curious and like to learn new things.
- You see solutions, not the problems!
- You are flexible and thrive on change
Your experience
- You have an analytical and critical thinking, if you have worked with consumer and market analysis before, it is even better!
- Academic university degree in data science, statistics, econometrics, mathematics, computer science, economics and / or civil engineering.
- 4+ years of experience working with Python/PySpark. Developing models and processes, creating integrated analytics modules.
- Expertise in organizing and refining raw data for analysis, coupled with ability to craft impactful data visualization.
- Ability to evaluate model performance and iterate on solutions for continuous improvement.
- Solid knowledge about statistical models and / or machine learning.
- You have good knowledge in both English and Swedish, verbal and written.
- Tech stack keywords: Python, PySpark, SQL, Github, Databricks, GCP, ML Flow
