Analyze sales trends and other KPI's such as sales volume, premiums, lead times etc, to obtain various insights into sales strategies and promotions.
Help sales forecast based on historical data, market trends, and seasonality to support demand planning.
Use predictive analytics to anticipate changes in demand patterns, helping the business adapt its sales and distribution approach.
Assistant defining data architecture and data pipeline requirements to ensure relevant data is collected and processed effectively.
Use data to provide insights into customer retention, churn analysis and cross selling or upselling opportunities.
Analyze large data sets to extract meaningful insights that drive business growth.
Create and maintain data models, dashboards, and reports to visualize scheme metrics.
Collaborate with various departments to understand their data needs and ensure accurate data collection.
Translate business requirements into analytical solutions for IT teams.
Train end users on reporting tools and data interpretation, enabling them to make data-driven decisions.
Maintain data mapping documents, business matrix and/or other data design artifacts that define business data requirements and transformation rules.
Work in an agile environment, adapting to changing requirements and collaborating with cross-functional teams.
Create and implement end-to-end testing plans, partnering heavily with the Sales and Distribution teams to consider downstream impacts and ensure data quality throughout the testing process.
Demonstrate a proactive approach to personal and professional development, with a commitment to learning and adapting in a dynamic business landscape.
Requirements
Bachelor's degree in data Analytics or Computer science or related field
6 years or more experience as a Business Data Analyst or in a similar role
Proficiency with data analysis tools like SQL, Python, Erwin Data Manager or similar data modelling tools
Experience with data visualization tools such as Tableau, Power BI, or similar platforms
Experience working with databases and data warehouses such as SQL Server, MySQL Oracle, or Snowflake
Familiarity with ETL (Extract – Transform - Load) processes
Strong analytical and problem-solving skills
Ability to translate complex data into clear insights and recommendations
Excellent communication skills with the ability to present data to non-technical audiences.
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