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Model N
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Data Analyst - Customer Analytics (Power BI, Python, Azure)

Data Analyst - Customer Analytics (Power BI, Python, Azure)

Model N

5 - 8 years

8 - 12 Lacs

hyderabad

Posted:2 days ago| Platform:

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Skills Required

data analysis automation data modeling business analytics analytical life sciences business intelligence operations crm sql

Work Mode

Work from Office

Job Type

Full Time

Job Description

Model N is seeking an experienced and innovative Business Intelligence Analyst to join our newly formed Client Analytics team. This is a unique opportunity to join at the ground level and contribute to building an analytics capability that delivers meaningful insights and value across the organization.
The ideal candidate will have proven experience integrating disparate data sources to deliver actionable insights, develop production-ready models, and create compelling dashboards and reports. A strong customer focus and the ability to independently manage multiple projects or workstreams are essential.

If you are passionate about turning data into business impact and thrive in a collaborative, fast-paced environment, we'd love to hear from you.

Job Responsibilities

Collaborate with stakeholders to gather and translate business questions into actionable analytics solutions that drive customer and business impact.
Lead end-to-end analytics projects, including scoping, data exploration, modeling, and delivery of findings through reports, presentations, and dashboards.
Develop and maintain dashboards and visualizations in Power BI to track key performance indicators, customer metrics, and operational trends.
Analyze customer data to uncover insights related to engagement, retention, segmentation, and lifecycle behaviors that inform business strategy.
Design and implement predictive models (eg, segmentation, churn propensity) using tools like Python and scikit-lear n, in collaboration with engineering for production support.
Validate data requirements and ensure accuracy, working closely with the data engineering team to ensure consistency, completeness, and usability across sources.
Leverage tools like Python and Azure Fabric to explore and prepare data for analysis and modeling; contribute to scalable analytics workflows with guidance from the data engineer.
Partner with cross-functional teams (Sales, Customer Success, Product) to align analytics with organizational goals and provide strategic insights.
Stay current with analytics and BI best practices, continuously improving analytical approaches, visualization techniques, and data storytelling.
Stay current with analytics and BI best practices, continuously improving analytical approaches, visualization techniques, and data storytelling.

5 8 years of experience in business intelligence, data analytics , or a related role.
Proven ability to deliver actionable insights from large, complex, and diverse datasets.
Experience working cross-functionally with business, product, and engineering teams to support strategic initiatives.
Familiarity with customer analytics concepts, including segmentation, churn analysis, and lifecycle metrics.

Technical Skills

Advanced proficiency in Power BI, including DAX, data modeling, and dashboard design .
Strong proficiency in Python for data analysis, statistical modeling, and automation.
Experience working with Azure Fabri c or other modern cloud-based data platforms.
Strong SQL skills for querying, joining, and transforming structured data.
Understanding of data warehousing concepts (eg, star schema, dimensional modeling); experience with platforms like Azure Synapse, Snowflake, or Redshift.
Exposure to CRM platforms (eg, Salesforce) and familiarity with version control tools (eg, Git).

Analytical Business Acumen

Solid foundation in descriptive and predictive analytics, including statistical methods and machine learning.
Ability to integrate, clean, and analyze data from disparate systems.
Skilled in translating complex data into clear narratives, actionable insights, and strategic recommendations.
bachelors degree in a quantitative, technical, or business field (eg, Statistics, Mathematics, Economics, Computer Science, Data Science, Business Analytics). masters degree preferred in Business Analytics, Data Science, or a related discipline.

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