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Senior Data Scientist

Stockholm, Stockholm County, Sweden

+44 (0) 1273311206 joe@quotacom.com

About This Opportunity

Quotacom are proud to be partnered with a leading business within Parcel Distribution and E-Commerce, based in Sweden.

With international presence, and over 20,000 employees, they are committed to leveraging data-driven insights to optimise operations and deliver exceptional customer experiences.

In addition, they are leading the way in integrating cutting-edge technology into their operations, such as AI and Machine Learning.

As part of their strategic growth plans, they are seeking a Senior Data Scientist.

The ideal candidate will possess expertise in Time Series Analysis, Forecasting, Optimisation, and Machine Learning. As a Senior Data Scientist, you will play a crucial role in driving data-driven decision-making processes, optimising operational efficiency, and enhancing our competitive edge in the market.

To learn more, please apply to this position, or email joe@quotacom.com with your CV to set up a confidential discussion.

At Quotacom, we take the security and privacy of your personal data very seriously, any data we hold will be in accordance with data protection legislation. Full details of our privacy notice can be found at www.quotacom.com/privacy-notice

Desired Skills and Experience

Forecasting and Prediction:

  • Develop and implement robust time series forecasting models to predict parcel flows and volumes in both short-term and long-term windows.
  • Utilise advanced machine learning techniques to enhance the accuracy and reliability of demand forecasts.
  • Generate actionable insights from forecasting models to support strategic and operational decision-making processes.

Optimisation and Decision Making:

  • Optimise resource allocation, route planning, and workforce management using mathematical optimisation algorithms.
  • Collaborate with cross-functional teams to design and implement optimisation solutions that maximise efficiency while minimising costs.
  • Drive continuous improvement initiatives by identifying areas for optimisation and implementing data-driven solutions.

Geospatial Analysis:

  • Leverage geospatial data to analyse and optimise parcel delivery routes, terminal operations, and network design.
  • Develop geospatial forecasting models to predict parcel demand and optimise service coverage across different regions.
  • Utilise geographic information systems (GIS) tools to visualise and analyse spatial data for strategic decision-making.

Data Science Engineering:

  • Collaborate with data engineers to design and deploy scalable data pipelines for processing, analysing, and visualising large volumes of data.
  • Utilise cloud-based platforms such as AWS, Azure, and Databricks to build and deploy data science solutions.
  • Implement best practices for data governance, version control, and model deployment to ensure reproducibility and scalability.

Employment Status

Full Time-Hybrid

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