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Applied Data Scientist

Nokia

Nokia

Data Science
Finland
Posted on Feb 5, 2026

The Patent Analytics team delivers data‑driven intelligence that powers the management of Nokia’s world‑leading patent portfolio. We are seeking a talented Applied Data Scientist to play a pivotal role in advancing our analytical capabilities across the entire patenting lifecycle.

In this role, you will design, develop, and scale analytical pipelines and data‑driven products that directly support patent portfolio management. Your work will span across advanced data engineering, analytical application development, patent‑domain data modeling, and AI‑enabled patent portfolio insights. You will help build and maintain analytical infrastructure relied upon by Patenting Units, Portfolio Operations, and other key stakeholders across the organization. To achieve this, you will collaborate closely with a dynamic, interdisciplinary team of data scientists, patent attorneys, and business strategists—driving innovative solutions that shape high‑impact decision‑making.

If you are an experienced patent data scientist with a strong analytical mind, a passion for solving complex business challenges, and the drive to excel in a global, fast‑paced environment, you may be the ideal addition to our exceptional team. The Patent Analytics team delivers data‑driven intelligence that powers the management of Nokia’s world‑leading patent portfolio. We are seeking a talented Applied Data Scientist to play a pivotal role in advancing our analytical capabilities across the entire patenting lifecycle.


Advancing connectivity to secure a brighter world.

Nokia is a global leader in connectivity for the AI era. With expertise across fixed, mobile and transport networks, powered by the innovation of Nokia Bell Labs, we’re advancing connectivity to secure a brighter world.



Our recruitment process

We act inclusively and respect the uniqueness of people. Our employment decisions are made regardless of race, color, national or ethnic origin, religion, gender, sexual orientation, gender identity or expression, age, marital status, disability, protected veteran status or other characteristics protected by law. We are committed to a culture of inclusion built upon our core value of respect.

If you’re interested in this role but don’t meet every listed requirement, we still encourage you to apply. Unique backgrounds, perspectives, and experiences enrich our teams, and you may be just the right candidate for this or another opportunity.

The length of the recruitment process may vary depending on the specific role's requirements. We strive to ensure a smooth and inclusive experience for all candidates. Discover more about the recruitment process at Nokia.


Some of our benefits in Finland:

  • Flexible and hybrid working arrangements to support work–life balance
  • A minimum of 90 days of Maternity and Paternity Leave based on eligibility
  • Edenred benefit voucher - 400€ per year
  • Annual bonus - based on individual and company performance
  • Health and well-being support - occupational health services, well-being programs, employee resource groups, reimbursement for spectacle lenses, life insurance and gyms at every site
  • Personal Support Service 24/7 – a confidential support channel open to all Nokia employees and their families in challenging situations
  • Share in Success – voluntary employee share purchase plan
  • Employee Referral program – reward yourself and support Nokia by referring a friend to apply to Nokia
  • Career growth & learning - technical career path, job rotation, coaching and digital learning platforms
  • Car benefit – the eligibility for a company car is based on employee’s job grade

The Patent Analytics team is seeking a highly skilled Applied Data Scientist to develop analytical insights and data driven evaluations to guide patent portfolio management: create performance metrics, dashboards, and predictive analyses to optimize patenting operations and support informed decision making across the patent lifecycle.
  • M.Sc. degree in a relevant field such as Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Technology or a related discipline.

  • 1+ years of experience as a data scientist with a focus on patent data analytics

  • Proficiency in designing, implementing, and maintaining scalable patent data pipelines.

  • Demonstrated experience building interactive dashboards and applications using modern frameworks such as Streamlit or React.

It would be nice if you also had:

  • Strong programming skills in languages such as Python

  • Experience with Data Extraction, Transformation, and Loading (ETL) frameworks to implement data pre-processing and/or post-processing.

  • Demonstrated ability to write high-quality, production-ready code (readable, well-tested, with well-designed APIs).

  • Experience with cloud services and analytical tools, preferably with Microsoft Azure platform (Databricks, Microsoft Fabric).

  • Knowledge of machine learning algorithms and deep learning architectures, particularly those used in LLMs (e.g., transformers, attention mechanisms).

  • Expertise in methods such as predictive analytics, time series, hypothesis testing, classification, clustering, and regression analysis.

  • Strong analytical skills to identify patterns, trends, and insights from complex datasets.

  • Excellent verbal and written communication skills to convey technical concepts to non-technical stakeholders.

  • Strong interpersonal skills to work effectively within a global, cross-functional team.

  • Flexibility to thrive in a fast-paced and dynamic working environment.

  • Willingness to continuously learn and adapt to new technologies and methodologies.


  • Design, implement, and sustain scalable data pipelines, interactive dashboards, and comprehensive reports to facilitate data-driven decision-making across teams.
  • Developing and implementing innovative analytical models that provide valuable insights into Nokia and competitor patent portfolio management.
  • Contributing to the development of analytical methods by incorporating technological advancements such as large language models (LLMs) and leveraging state-of-the-art tools.