
Product Data Strategist
1 day ago
Are you passionate about leading a team that's driving innovation in the fashion retail industry? As a leader in our Tech organization, you'll be responsible for guiding your team towards excellence in data analysis and product development.
Job DescriptionThe Engineering Team Lead has a dual focus – staff responsibility and strategic contribution to Product Data Analytics management initiatives. With staff responsibility for Data Analysts within the AIAD tech center product teams, you'll guide your team on competence-specific conversations, support resource allocation, and help build & improve WoW with Data Analytics.
As an Engineering Team Lead, you'll work closely with product managers, program managers, and other EMs to secure the right competencies and skillsets across the Data Analyst community. You'll collaborate with stakeholders in other product teams/areas and enabling functions, building a broad network within Business Tech.
With a strong customer focus, commercial mindset, and innate curiosity, you'll thrive in an organization that heavily relies on making data-driven decisions. By coaching and supporting your team members' growth, you'll play a pivotal role in shaping the future of analytics across the fashion retail value chain.
Qualifications- Previous experience in leadership and staff responsibility is essential.
- Ability to coach others in a way that enables them to grow professionally and increase their performance.
- Ability to engage people in high achievements and support them by creating conditions for personal growth.
- Academic degree within Engineering, Business Administration, Economics, or similar.
- At least 5-7 years of experience in data analysis, product/business analysis, or similar.
- Experience in working with programming/querying languages such as SQL, R, or Python.
- Experience in working with data visualization tools e.g. Power BI, Tableau, or Looker.
- Good understanding of using numerical, statistical, and analytical methods to apply to data processing.
- Great business acumen to guide the Data Analyst team on the value contribution to the success of H&M.
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