What's in it for You:
1. Career evolution – continuous training & learning opportunities
2. A supportive team environment where everyone is working toward the same goal
3. Participation in exciting and motivating projects
4. A competitive salary
5. Flexible working and hybrid model of working
6. Number of annual leave day based on your work experience
7. Life insurance and private health insurance for your children and yourself
8. Holiday Allowance
9. A strong open-door policy within management
10. LinkedIn Learning license
11. Fitpass Premium subsidy
12. At Avnet, values such as integrity, customer service, responsibility, teamwork and innovation are highly valued.
Main Purpose and Goal:
13. The team lead for Data Science in EMEA will be responsible for managing a team of Data Scientists.
14. The role is responsible for overseeing the design, development, and implementation of ML models and analytical models
15. The role is to plan project milestones and keeping track of timelines to contribute to the overall success of the organization’s data initiatives.
16. The role is to identify, qualify and define new opportunities in the area of modern data utilization.
17. The role is to continuously ensure alignment with business priorities
18. The team lead is responsible to guide and motivate the team
Main Tasks and Responsibilities:
19. Leadership and Team Management:
20. Provide effective leadership and mentorship to a team of data scientists, fostering a collaborative and high-performing work environment.
21. Set clear performance expectations, roles and responsibilities, and conduct regular performance evaluations to support team members' growth and development.
22. Encourage knowledge sharing and continuous learning to keep the team up-to-date with the latest technologies and industry best practices.
23. Ensure redundancy in the organisation to business support during holidays and illness.
24. Management of Data Solutions in EMEA
25. Oversee the design and implementation of robust data transformation processes to ensure data availability and accessibility for data science purposes.
26. Collaborate with cross-functional teams to understand data requirements and design data architecture to support business needs.
27. Ensure data quality, data governance, and data security standards are adhered to across all data science activities.
28. Define, prioritize and monitor appropriate requirements and continuously review the process.
29. Participate in innovation related projects and implementation.
30. Provoke, challenge and feed the organization with new and modern ways of data usage in alignment with Analytics and Process Management in the organization.
31. Lead business requirements gathering, solution design and documentation.
32. Ensure compliance with data protection and data security policies.
33. Encourage best practise sharing and standardisation between the speedboats.
34. Ensure effective and efficient internal processes.
35. Application Ownership
36. Overall ownership and responsibility for Data science solutions in EMEA
37. Own setup and maintenance of data and model architecture
38. Stay ahead of emerging technologies and industry trends in data engineering and data science to identify opportunities for improvement and innovation.
39. Evaluate and recommend suitable data tools, frameworks, and platforms to enhance the team's capabilities and improve overall efficiency.
Additional Tasks
40. Enablement Initiatives
Develop and execute enablement initiatives to develop skills within various business units
Support knowledge transfer in BI and Process Mining teams
41. Project Management
42. Lead the planning, execution, and delivery of data engineering and data science projects within agreed timelines and budgets.
43. Track project progress, manage risks, and communicate project status and outcomes to stakeholders.
Profile:
44. Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field. Advanced degrees are a plus.
45. Proven experience 5+ years in data engineering, data science, or a combination of both
46. Strong expertise in data engineering tools and technologies (SQL, ETL frameworks, data warehousing) and data science libraries (e.g., Python, R).
47. Familiarity with cloud-based data platforms and services (e.g., AWS, Azure, Google Cloud) and big data technologies is preferred.
48. Experience in building and deploying machine learning models and predictive analytics solutions.
49. Excellent analytical and problem-solving skills with a keen attention to detail.
50. Effective communication skills with the ability to convey technical concepts to non-technical stakeholders.
51. Ability to foster a collaborative and innovative work environment.
52. Strong project management skills, with the ability to prioritize tasks and manage multiple projects simultaneously.
53. A passion for leveraging data to drive business outcomes and improve operational efficiency.
54. Strong interpersonal skills, persuasive power and a team player.
55. Fluent in English
56. Project management basics
Authorities:
57. First Escalation level in terms of Data Science set-up
58. Data Science decision making.
The above statements are intended to describe the general nature and level of work being performed. They are not intended to be construed as an exhaustive list of all responsibilities, duties, and skills.