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Enterprise Insights & Analytics Analyst (Work Timings :- 03:30 PM IST to 12:30 AM IST)

Tungsten Automation - Hyderabad, Telangana, India - In-office

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Tungsten Automation is seeking an Enterprise Insights & Analytics Analyst to join their Hyderabad office. This role focuses on leveraging data to generate actionable insights that drive business decisions across the organization. Key responsibilities include collecting, analyzing, and interpreting data from various sources to identify trends, patterns, and opportunities for business improvement. You will partner with stakeholders across teams to understand business needs and deliver insights that support strategic decision-making. The role involves building dashboards and visual reports using tools like Tableau or Power BI to present complex data in accessible formats. You will define and track key performance indicators (KPIs) aligned with company objectives, and apply statistical methods, machine learning algorithms, and forecasting models to predict future trends. Collaboration with IT, data engineering, and analytics teams ensures data quality, availability, and integrity. The position also includes identifying opportunities to improve data processes, reporting tools, and analytics methodologies. A notable aspect of this role is the integration of AI-enabled tools—such as chatbots, documentation automation, and analytics assistants—to improve efficiency and accuracy while adhering to company AI governance and data privacy standards. You will develop skills in prompting AI systems, assessing output quality, and leveraging AI to ideate and scale solutions. Required qualifications include a bachelor's degree in Data Science, Statistics, Business Analytics, Computer Science, or a related field (master's degree preferred). You need strong SQL knowledge for querying and manipulating data, experience with data visualization tools, and 2-4 years of analytics or related experience. Programming language proficiency is a plus. Critical soft skills include the ability to derive meaningful insights from large datasets, think critically, communicate insights to both technical and non-technical audiences, and manage multiple projects in a fast-paced environment.

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