• Develop advanced analyses, dashboards, analytical models, and data-driven intelligent solutions, turning information into actionable insights to support strategic decision-making; • Build, evolve, and maintain analytical solutions, automations, internal products, and data- and AI-driven applications, using AI-assisted development and tools such as Windsurf or similar; • Operate within an AI-driven operating model, using LLMs, Generative AI, prompt engineering, intelligent agents, and automations to accelerate analysis, code generation, documentation, investigations, and the continuous improvement of the team's solutions; • Work on data extraction, cleansing, integration, and preparation for analytical consumption and intelligent models, interacting with data pipelines, data architectures, and enterprise analytics environments; • Apply best practices in governance, versioning, MLOps, data quality, and data security, also contributing to the advancement of the team's analytical culture and the use of Artificial Intelligence; • Digital mindset, curiosity about new technologies, and an interest in understanding how Artificial Intelligence can transform processes, experiences, and outcomes.

• Analyze performance data across a large and diverse client portfolio to identify trends, patterns, and opportunities • Own and evolve portfolio level performance reporting, including dashboards and scorecards • Build and maintain benchmarking frameworks to compare performance across key verticals • Define and standardize KPIs to ensure consistency across teams • Evaluate the effectiveness of strategies and product capabilities, identifying what drives the strongest outcomes • Conduct post launch analyses for product and strategy updates impacting performance • Support emerging areas like AI driven search such as AI assisted search visibility, entity coverage, and local signals as measurement capabilities evolve • Partner with Product, Data, and Engineering teams to improve data quality and expand access to meaningful signals • Translate complex data into clear narratives and recommendations for both technical and non technical stakeholders • Proactively surface insights and opportunities that influence product direction and business strategy

• Perform deep data analysis to identify trends, anomalies, variances, and forecasting improvement opportunities. • Support senior data scientists with model inputs, backtesting, validation, and performance analysis. • Monitor forecast accuracy, bias, and overall health of forecasting solutions. • Analyze data quality issues and understand business drivers. • Build analytical datasets and reports to support forecasting and supply chain planning. • Develop dashboards and KPI reporting using Power BI or similar analytics platforms. • Collaborate with business teams and data scientists to improve decision-making. • Automate recurring analysis using SQL and Python. • Ensure strong data governance and reliable data availability.

• Lead Data Analyst needed in New York, NY and various unanticipated locations throughout the U.S. Utilize the power of solutions that can be driven through Visualization and ETL tools. • Establish connection with different teams to evaluate the automation and service management offerings Python can bring in. • Drive discussions with various teams to foresee opportunities to unify the operations console across businesses. • Implementation of Customer Dashboard and Reports for real-time performance view of SLA. • Work on SQL Server (or client specific RDBMS) developing customized codes and testing. • Responsible for creating operational insights for telecom network related data from Fuze and integrate with other data sources to identify revenue growth/cost optimization/operational efficiency opportunities. • Interpret data and define new KPIs for data analysis from multiple sources. • Use data visualization and other data-gathering methods to either provide internal strategic direction or guide decisions for other teams for new tower builds, OFS analysis, Fallout analysis, compliance and usage adoption. • Work on acquiring data from primary or secondary data sources and preserve the data integrity of these sources using SQL, Python and other analytical tools. • Create powerful data visualizations using tools like Tableau and Looker. Focus on the overall service quality and timely execution of the project. • Active participation and contribution to all service improvement initiatives to ensure they are aligned to our customers’ expectations. • Successfully implement multiple Analytics/IT projects by providing the technology knowledge and vision to support the company’s business objectives and evaluate and recommend all software for business processes. • Be accountable for all aspects of service delivery in conceptualization, planning, design, automation, transition, and delivery. • Understand clearly operational definitions for all processes; understand how to measure all critical data points in the processes, improve any irregularities reported because of the Metrics Dashboards. • Proactively initiate Process Improvements keeping in mind inputs from Audit Process. Manage Process & Framework.