OPS Data Scientist

Job Description

Join our Operational Analytics team as a Data Scientist, where you'll play a pivotal role in harnessing the power of data to uncover strategic insights and drive tangible business growth. As a key member of the Ops Data & Analytics team, consisting of three analysts and one data scientist, you'll be at the forefront of transforming raw data into intuitive insights.

This role primarily focuses on text analysis, speech-to-text analysis, and other predictive analysis, ensuring alignment with those who have a keen interest in these specific areas.

Utilize advanced statistical and machine learning techniques to analyze extensive datasets, extracting actionable insights. Engage with cross-functional teams to identify business challenges, fostering collaborative efforts to develop data-driven solutions that optimize customer processes and enhance operational efficiency.

Main tasks and responsibilities:

• Apply advanced statistical and machine learning techniques, with a primary focus on text analysis, speech-to-text analysis, and other predictive analysis.
• Collaborate with cross-functional teams to identify business challenges, developing data-driven solutions to optimize customer processes and drive operational efficiency.
• Design and implement predictive models and algorithms for forecasting, anomaly detection, and decision-making.
• Develop and maintain data pipelines, ensuring data quality and integrity throughout the data lifecycle.
• Present findings and recommendations in a clear and concise manner to facilitate informed decision-making.
• Stay updated on the latest industry trends and emerging technologies in data science and analytics.

Skills & Requirements

• A bachelor's or master's degree in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, or a related discipline.
• Strong proficiency in programming languages such as Python or R, with experience in data manipulation, analysis, and visualization.
• Solid understanding of statistical concepts and experience applying statistical modeling techniques.
• Experience with machine learning algorithms, data mining, and predictive modeling.
• Familiarity with databases and SQL for data extraction and manipulation.
• Excellent problem-solving abilities and attention to detail, with the ability to work independently or as part of a team.
• Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders effectively.

Experience:

• Experience as a data scientist, data engineer, data specialist or data analyst.
• A strong track record of building and deploying predictive and/or prescriptive models.
• Proven programming and modelling expertise.
• Experience with cloud platforms, such as AWS or Azure, is a plus.
• Prior experience in customer analytics or process optimization is advantageous but not mandatory.

What we offer

• An opportunity to work in a large, high-performing international company, in a dynamic environment that is constantly changing.
• A corporate culture that is professional and dynamic, yet informal. Bureaucracy is kept to a minimum, as we expect our skilled employees to make long lasting and impactful decisions to shape our future.
• Highly competent, dedicated, and friendly co-workers with strong collaboration across the Nordics.
• Hybrid work environment (2-3 days remote work per week).
• Emphasis on work-life balance.
• Anticipated travel activity of 2-3 times per year, each trip lasting a few days.
• Opportunity to work with the latest technologies in machine learning and AI.

This position can be in any of our Nordic locations in Helsinki, Hvidovre, Solna, Stavanger or Lysaker.

Are you interested?

If you are intrigued by this position and possess the right profile and mindset, please submit your application and CV via the link. Applications will be reviewed continuously, and interviews will be planned as soon as a suitable candidate is identified.

If you have any questions about the position, you can contact Philip Aarup, Team Leader of OPS Data & Analytics.