Data Analytics Team Manager

What Makes a Honda, is Who makes a Honda
Honda has a clear vision for the future, and it’s a joyful one.  We are looking for individuals with the skills, courage, persistence, and dreams that will help us reach our future-focused goals. At our core is innovation. Honda is constantly innovating and developing solutions to drive our business with record success.  We strive to be a company that serves as a source of “power” that supports people around the world who are trying to do things based on their own initiative and that helps people expand their own potential. To this end, Honda strives to realize “the joy and freedom of mobility” by developing new technologies and an innovative approach to achieve a “zero environmental footprint.”

We are looking for qualified individuals with diverse backgrounds, experiences, continuous improvement values, and a strong work ethic to join our team.

If your goals and values align with Honda’s, we want you to join our team to Bring the Future

The role of a Data Analytics Team Manager is to lead and manage a team of data analysts and/or data scientists in extracting insights and providing valuable analytics to support data-driven decision-making within an organization. Here are some Data Analytics Team Manager key responsibilities:

• Team Leadership: Manage and provide leadership to a team of data analysts or data scientists, ensuring effective collaboration and coordination among team members. Set clear goals, provide guidance and mentorship, and evaluate individual and team performance.
• Data Analysis Strategy: Develop and execute a data analysis strategy that aligns with the organization's overall business objectives. Define the scope, approach, and methodologies for data analysis projects, considering the available data sources and tools.
• Data Exploration and Visualization: Guide the team in exploring and analyzing large datasets to uncover insights, trends, and patterns. Ensure effective data visualization techniques are utilized to present findings in a clear and concise manner to stakeholders.
• Statistical Analysis and Modeling: Oversee the development and application of statistical techniques, machine learning models, or predictive modeling to derive actionable insights from data. Collaborate with data scientists or statisticians to develop robust analytical models.
• Data Quality and Validation: Ensure the team follows best practices for data quality assurance, including data cleansing, validation, and integrity checks. Implement processes and controls to maintain data accuracy and reliability.
• Business Stakeholder Engagement: Engage with business stakeholders, including executives, managers, and end-users, to understand their analytical needs and provide strategic recommendations. Collaborate with cross-functional teams to define analytical requirements and priorities.
• Data Governance and Compliance: Ensure compliance with data governance policies, procedures, and legal regulations. Collaborate with data governance teams to define data standards, privacy measures, and data usage policies.
• Tool and Technology Evaluation: Stay updated with the latest data analytics tools, technologies, and methodologies. Evaluate and select appropriate tools or platforms to support the team's analytical needs, ensuring scalability and usability.
• Reporting and Presentation: Oversee the creation of reports, dashboards, and presentations to communicate analytical findings and insights to stakeholders. Ensure the delivery of actionable and impactful insights that drive informed decision-making.

• Work together with Unit and Dept leadership to develop and deliver long-term strategic goals for business intelligence and data sciences roadmaps; sense, study, test and implement new technologies and manage overall knowledge in data sciences and business intelligence spaces.
• Build, lead, and manage high performance team of business intelligence and data sciences to meet organizational data strategy and deliver project with quality and customer service focus. Foster associate development by coaching, training, and mentoring.
• Establish and lead enterprise analytics governance methods, stewardship and procedures for tracking quality, completeness, redundancy, and improvement. Develop and promote cloud analytics strategy.
• Build NA & global relationships and network to achieve trust and credibility by discovering and meeting the needs of internal and external customers and vendors. Use persuasion and influence to achieve maximum results with Enterprise IT goals.

Hybrid: 2 to 3 days per workweek at the Marysville, OH office

#LI-Hybrid

#LI-BEV

Education: College degree in computer science, information systems, or computer engineering, alongside Certification(s) in Analytics, Data Science and Business Intelligence tools and technologies

• Overall ~ 8 or more years in IT of which 3+ years of experience leading teams in Data Engineering, Data scientist, Data Analysis, Information Management and Business Intelligence
• Experience is strategy, project, financial, performance and operations management.
• Knowledgeable, go-getter, self-driven individual with strong sense of ownership.
• Team player/collaborator who builds relation with customers and team members, earns their trust and creates influence to meet tactical or strategic objectives.
• Servant leader who clears roadblocks for the team members to meet their deliveries and help them grow individually.
• Knowledge of project management, budgeting, financial management, vendor management, service management and operational efficiency will be a huge plus.
• Strong knowledge and experience developing strategies, roadmaps and lifecycle plans for analytics.
• Strong oral, verbal communication/presentation skills.
• Strong understanding of relational data structures, theories, and principles.
• Strong technical knowledge and implementation experience in the areas of analytics, business intelligence platforms, solutions and architectures
• Experienced in BI tools like Power BI, Tableau, SAP Cloud Analytics and SAP Business Objects.
• Knowledge in Data Sciences area including ML models, algorithms, data wrangling, Data Ops etc.
• Experience with SQL or database platforms like MS SQL Server, PostgreSQL etc.
• Knowledge of cloud-based technology including cloud connectivity options, data storage options (S3, Glacier), data lakes (S3 etc.), master data management, data cataloguing, cloud warehouses (Redshift, etc.), cloud ETL/ELT tools, cloud databases (RDS, DynamoDB etc.), and cloud/on-prem BI products (Power BI, Tableau, etc.)

What differentiates Honda and makes us an employer of choice?

Total Rewards: 
•    Competitive Base Salary (pay will be based on several variables that include, but not limited to geographic location, work experience, etc.)
•    Regional Bonus (when applicable)
•    Manager Lease Car Program (No Cost - Car, Maintenance, and Insurance included)
•    Industry-leading Benefit Plans (Medical, Dental, Vision, Rx)
•    Paid time off, including vacation, holidays, shutdown
•    Company Paid Short-Term and Long-Term Disability 
•    401K Plan with company match + additional contribution
•    Relocation assistance (if eligible)

Career Growth:
•    Advancement Opportunities
•    Career Mobility  
•    Education Reimbursement for Continued learning
•    Training and Development Programs 

Additional Offerings:
•    Lifestyle Account
•    Childcare Reimbursement Account
•    Elder Care Support
•    Tuition Assistance & Student Loan Repayment
•    Wellbeing Program
•    Community Service and Engagement Programs
•    Product Programs
•    Free Drinks Onsite

Honda is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, creed, religion, national origin, sex, sexual orientation, gender identity and expression, age, disability, veteran status, or any other protected factor.