Data Scientist

We are looking for an experienced Data Scientist to join our team and collaborate closely with our Data Engineers on building advanced analytics and reporting solutions. You will play a pivotal role in understanding business needs, particularly within the distribution vertical, and translating those into complex reporting, dashboards, and AI-driven insights.

Your expertise in working with large, complex datasets and your deep knowledge of finance analytics will be crucial in delivering value to our ERP customers.

Excellent communication and problem-solving skills to collaborate effectively with the team are essential. You should have the willingness to learn new technologies to continuously improve data science practices.

This is a fully remote or hybrid role embedded with our client, a Swedish supply chain company.

Responsibilities

1.  Collaborate with Data Engineers: Work closely with Data Engineers to leverage the data Lakehouse architecture on Databricks, ensuring that data is structured and optimised for analytics and reporting.
2. Business Requirement Analysis: Engage with business stakeholders to understand their needs and translate these into detailed analytics and reporting requirements. Develop complex reporting products and dashboards that provide actionable insights.
3. Advanced Analytics and Reporting: Design and build sophisticated analytics models and visualisations using large and complex datasets. Create and maintain dashboards that deliver key metrics and insights to the business, particularly focusing on the needs within the distribution vertical.
4. Finance Analytics Expertise: Apply your deep understanding of finance analytics to create solutions that meet the specific needs of financial departments within distribution companies. Provide insights and reporting that support financial decision-making.
5. AI and Machine Learning Solutions: Develop, train, and deploy AI models that deliver predictive analytics and automation for multiple customers. Focus on creating AI solutions that cater to the unique needs of the distribution sector.
6. Data Management: Work with large, complex datasets from ERP systems, ensuring data quality and integrity. Utilise advanced data analytics techniques to process, analyse, and interpret data.
7. Industry Expertise: Leverage your experience in the distribution vertical to tailor analytics solutions that address industry-specific challenges and opportunities.
8. Stakeholder Communication: Communicate complex technical concepts to non-technical stakeholders, providing clear explanations and visualisations that support business decision-making.
9. Stay Current with Industry Trends: Keep up to date with the latest developments in data science, AI, and analytics tools and methodologies, especially as they pertain to the distribution and finance sectors.

Requirements

1.  Education and Experience: At least 5 years of experience in data science, with a focus on analytics and reporting for ERP customers (ideally in the distribution vertical).
2. Technical Expertise: Proficiency in data science tools and languages such as Python, SQL, and Apache Spark. Experience with Databricks and familiarity with the Azure ecosystem, including ADLS G2 and ADF.
3. Analytics and Reporting Skills: Strong experience in designing and building dashboards and analytics reports. Proficiency in visualisation tools like Power BI, Tableau, or similar.
4. Finance Analytics Knowledge: Deep understanding of finance analytics, including the ability to create models and reports that support financial decision-making.
5. AI and Machine Learning: Proven experience in developing and deploying AI and machine learning solutions, particularly in a multi-customer environment within the distribution vertical.
6. Complex Data Management: Experience in handling and analysing large, complex datasets, particularly from ERP systems. Strong understanding of data structures and data quality management.
7. Communication Skills: Excellent communication skills with the ability to translate complex data and analytics into clear and actionable insights for business stakeholders.
8. Problem-Solving Skills: Strong analytical and problem-solving skills, with the ability to develop innovative solutions to complex business challenges.
9. Team Collaboration: Ability to work effectively as part of a cross-functional team, collaborating with Data Engineers and other stakeholders to deliver comprehensive data solutions.
10. Adaptability and Learning: Willingness to learn new technologies and stay abreast of industry trends to continuously improve data science practices.

Sounds interesting? We are excited to get to know you!

If you have any questions you would like to ask or if there is any additional information you would like to receive, please feel free to get in touch via [email protected].