Job Title: Director, Advanced analytics.

Reports to: Chief Data Officer – USA/ Canada

Department: EDO (Enterprise Data Office)

Status: Full Time, Exempt

Location: USA

Job Summary:

We are seeking a highly experienced and hands-on Director of Advanced Analytics to lead our analytics team and drive data-driven insights and strategies. The successful candidate will be responsible for developing and executing our advanced analytics strategy, managing the analytics team, and working closely with cross-functional teams to identify opportunities for data-driven insights. The ideal candidate should have a strong background in statistical modeling, machine learning, and predictive analytics, with a passion for using data to drive business growth. Additionally, they should be a strong leader with the ability to inspire and motivate teams to achieve business objectives while also contributing as a hands-on member of the team.

Key Responsibilities:

1. Develop and execute the company's advanced analytics strategy.
2. Manage the advanced analytics team, including hiring, training, and performance management.
3. Work closely with cross-functional teams to identify opportunities for data-driven insights.
4. Experienced building Data Journeys, data modeling, Data Design and architecture
5. Design and implement advanced analytics tools and processes to support business decisions.
6. Ensure data accuracy, security, and compliance by developing and implementing data governance policies and procedures.
7. Monitor and report on key performance indicators (KPIs) related to advanced analytics.
8. Stay up-to-date on emerging trends and technologies in advanced analytics and evaluate their potential impact on the business.
9. Develop and manage budgets for advanced analytics initiatives.
10. Communicate effectively with senior management and stakeholders to ensure alignment and support for advanced analytics initiatives.
11. Contribute as a hands-on member of the analytics team to drive data insights and deliver on key initiatives.

Required Tools:

1. Statistical software such as R or SAS for data analysis and modeling
2. Big data technologies such as Hadoop and Spark for data processing and storage
3. Business intelligence tools such as Tableau or Power BI for data visualization and reporting
4. Programming languages such as Python or Java for building custom analytics solutions.
5. Cloud-based platforms such as AWS, Snowflake or Azure for scalability and flexibility in analytics infrastructure
6. Data management tools such as SQL Server or Oracle for managing large and complex data sets
7. Collaboration and project management tools such as Azure DevOps, Jira or Trello for effective team communication and project tracking

Qualifications:

1. Bachelor’s or master’s degree in a related field (e.g., statistics, mathematics, computer science or any relevant area)
2. 8+ years of experience in advanced analytics, with at least 4 years in a leadership role.
3. Strong knowledge of statistical modeling, machine learning, and predictive analytics.
4. Hands-on experience with Visualization tools (Power BI, Tableau) Cloud computing technology (AWS, Azure, Snowflake) and statistical software.
5. Experience with big data technologies such as Hadoop and Spark
6. Strong leadership skills, with the ability to motivate and inspire teams to achieve business objectives.
7. Excellent communication skills, with the ability to communicate complex data insights to both technical and non-technical audiences.
8. Strategic thinking and problem-solving skills, with the ability to develop and execute long-term advanced analytics strategy.
9. Experience in managing budgets and financial reporting for advanced analytics initiatives.
10. Proven track record of delivering successful advanced analytics projects.
11. Ability to work hands-on with the analytics team to contribute to data insights and deliver on key initiatives.

Note: This job description is not intended to be all-inclusive. The employee may be required to perform other related duties as negotiated to meet the ongoing needs of the organization.

Tools:

1. Analytics and Business Intelligence Tools:
2. These tools are essential for data analysis, visualization, and reporting. Examples of such tools include Power BI, Tableau, Google Analytics, and Adobe Analytics.
3. Data Science Tools:
4. Data science tools are essential for advanced data analysis, machine learning, and predictive analytics. Examples of such tools include Python, R, SQL, Hadoop, Snowpark, Shiny and Spark.
5. Cloud Computing & Data Platforms:
6. Cloud computing platforms like Amazon Web Services (AWS), Microsoft Azure, Snowflake and Google Cloud Platform (GCP), Snowflake, Synapse to provide the necessary infrastructure and resources to manage and store large datasets.
7. Digital Transformation Tools:
8. Digital transformation tools like agile development frameworks (Scrum, Kanban), user experience design tools (Adobe XD, Sketch), and content management systems (WordPress, Drupal, Joomla) help organizations to drive innovation and improve customer experience.

Collaboration and Communication Tools:

1. Collaboration and communication tools like Slack, Microsoft Teams, and Trello are essential for project management and team collaboration.
2. Customer Relationship Management (CRM) Software:
3. CRM software like Salesforce and HubSpot help organizations to manage customer interactions and improve customer engagement.

Martech Stack:

1. Iterable, Marketo, SFMC, Google Analytics and Eloqua help organizations to automate marketing processes and improve marketing effectiveness.

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