We're looking for a Senior Data Scientist to join our India analytics team and build the data infrastructure, insights, and predictive models that power our next generation of customer intelligence and operational analytics.

You'll transform disparate datasets into clean, scalable data models and deliver dashboards, APIs, and predictive tools that help teams make faster, smarter decisions across support, operations, and customer engagement.

What Youll Do:

Build Core Data Pipelines & Models:

- Design and implement scalable data pipelines that ingest, clean, and transform data from Zendesk, customer systems, business tools, and third-party sources.

- Build curated, analytics-ready data models in Azure using Data Lake, Blob Storage, SQL, and related services.

- Develop robust ETL/ELT workflows that ensure data accuracy, timeliness, and consistency.

- Create reusable data layers and semantic models that power Power BI dashboards and analytics solutions.

- Implement data quality checks, validation rules, and monitoring to maintain high reliability.

Power BI Dashboards & Visualization:

- Build interactive, executive-ready Power BI dashboards that surface customer insights, performance metrics, and operational trends.

- Translate complex datasets into intuitive visual stories that make insights obvious and actionable.

- Optimize Power BI datasets for performance, refresh efficiency, and scalability.

- Define KPIs, metrics, and business logic in partnership with product, support, and operations teams.

- Maintain visualization standards, templates, and best practices across the company.

API Development & Data Products:

- Create APIs and data services that expose cleaned and modeled data to internal teams and applications.

- Design and document data contracts enabling analytics consumption across product, engineering, support, and business systems.

- Build lightweight data transformation layers that normalize customer, ticketing, and operational data.

- Implement authentication, authorization, and data-access controls to protect customer information.

- Work closely with engineering teams to integrate your analytics outputs into production workflows.

Predictive Modeling & Advanced Analytics:

- Develop predictive models for churn, support volume, ticket routing, customer satisfaction, or operational forecasting.

- Use statistical analysis and machine learning to identify trends, anomalies, and optimization opportunities.

- Build experimentation frameworks (A/B testing, causal analysis) to measure the impact of product or process changes.

- Create automated scoring pipelines that feed dashboards, alerts, or downstream systems.

- Drive analytical insights that shape product strategy, support operations, and customer engagement.

Collaboration & Delivery:

- Partner with support teams to translate Zendesk and customer data into actionable insights.

- Work closely with product and business stakeholders to define metrics, KPIs, and data-driven decision frameworks.

- Collaborate with engineering and DevOps teams on data pipeline deployment, monitoring, and resource management.

- Participate in architecture discussions, design reviews, and planning sessions.

- Move quickly from requirements to working analytics solutionsspeed and iteration matter.

- Support production analytics systems and troubleshoot data issues when they arise.

Quality & Best Practices:

- Write clean, reusable, well-documented data transformations, measures, and model logic.

- Implement robust logging, monitoring, and alerting for all data processes.

- Build unit tests, validation rules, and automated checks to ensure analytics reliability.

- Maintain clear documentation for datasets, dashboards, APIs, and architectural decisions.

- Contribute to data governance, modeling standards, and analytics best practices as we scale.

Knowledge, Skills, And Abilities:

- 5-8 years of professional experience in data science, analytics engineering, or BI development.

- Strong experience building Power BI dashboards, data models, and enterprise-grade visualizations.

- Solid understanding of Azure data services (Data Lake, Blob Storage, Azure SQL, Synapse, ADF, etc.

- Experience working with disparate datasetsticketing, customer, business, operational, and third-party sources.

- Knowledge of Zendesk data structures and support analytics is a strong plus.

- Experience designing and building APIs to expose analytical datasets.

- Strong SQL skills and familiarity with data modeling (star schema, DAX, M/Power Query).

- Experience with Python or R for data processing and predictive modeling.

- Understanding of machine learning basics, forecasting, or classification models.

- Knowledge of data governance, quality, and security best practices.

- Strong problem-solving, debugging, and data-storytelling abilities.

- Experience with Git and collaborative development workflows.