Regional Analytics Manager

ROLE & RESPONSIBILITIES

Customer and User Experience

1. Lead the analysis of customer experience (phygital; i.e., physical interactions & digital SaaS) success metrics to extract actionable insights, develop predictive models, and present executive-level reports on trends and their business impact.
2. Work with Executives and Business Leaders to calibrate business against the objectives and key results, forecast and report the state of the business for the assigned customer experience journey.
3. Identify key drivers of customer and user satisfaction, and work with product and customer teams to develop strategies to address pain points, and lead initiatives to close the feedback loop with customers and users.
4. Enable the implementation of customer experience success metric improvements, develop customer and user retention programs, and incorporate feedback into physical business process and digital SaaS enhancements.

Insights & Data Driven decision Making

1. Create business and customer reports that facilitate data-driven decision making. Build reports, dashboards, and metrics to monitor the performance of our offerings
2. Data mining, statistical analysis, and data visualization to help understand how customers (farmers) are interacting with our businesses (seeds, crop protection, crop solutions & services, and digital)
3. Own the design, development, and maintenance of ongoing reports, dashboards, etc. Maintain and continuously add to a robust reporting framework with dashboards and extensible emailers and notifications
4. Improve accuracy and coverage (instrument as many things as possible) of data.
5. Stay abreast of industry best practices, implement innovative approaches to gathering and utilizing customer feedback, and continuously refine customer experience metric methodologies.

Pipeline

1. Maintain and improve data pipeline including instrumentation.
2. Optimize for efficiency in being able to read data and summarize reports.
3. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies

KEY WORKING RELATIONS:

Internal

1. Direct to Farmer mission teams in India, Bangladesh, Indonesia, Philippines, Vietnam, Thailand, and Pakistan.
2. Digital New Value Businesses
3. Product and Customer facing teams in clusters and regions
4. Technical Community (e.g., Engineers and Data Scientists)

External Partners: Software & Analytic agencies

WHO YOU ARE:

1. Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field.
2. 5+ years of relevant experience in customer experience management, data engineering, data science, analytics, or a related field, with hands-on experience in data and product analytics.
3. Experience in developing business requirements and defining metrics for reporting, along with proficiency in data visualization tools (Preferably- Power BI, & Tableau, Looker etc).
4. Strong background in data analysis and interpretation. Experience with business intelligence front-end, data analytics middleware, or back-end data warehouse technologies.
5. Understanding of data analytics technology stack (e.g., Amazon Quicksight, Google Analytics, Hadoop/Spark, Columnar data warehouses, data streaming, ETL and data governance, predictive analytics, data science framework, etc.).
6. Strong proficiency in SQL and Python, with experience in building and optimizing AWS Glue pipelines for large-scale data processing.
7. Ability to engage and influence executive stakeholders as a business advisor and thought leader in data and analytics. Excellent written and oral communication skills, with the ability to effectively present technical concepts to both technical and non-technical stakeholders.
8. Excellent business acumen and problem-solving skills.

Good to have / Preferred:

1. Master's degree in Customer Experience Management, Business Analytics, or similar field preferred
2. 3+ years experience in social media insights and customer experience metrics and methodologies preferred.
3. Experience with AWS cloud services: EC2, EMR, RDS, Redshift. Understanding of Google Cloud Data and Analytics offerings (e.g., BigQuery, Looker, Dataproc, Pub/Sub, etc.) preferred.
4. Familiarity with applied statistics and controlled experiments is a plus.
5. Experience in data pipeline and workflow management tools, with the ability to design, develop, and maintain scalable data pipelines is a plus.
6. Incorporating GenAI tools to analytics & insights a plus.