Assistant Manager_Senior Engineer_Machine Learning, DevOps, GCP_Pune 42 views

Description

The Data Analyst will support their functional area across Vodafone Business Platform Solutions (VBPS) and generate insights by supporting fact-based decision making using business data. This includes implementing and managing data elaboration flows with a view to provide KPIs, metrics, trends and visual (digital) storyboards using a variety of technologies and analytical techniques. Working with the operational teams to target areas of opportunity or improvement and maximise business value through combining web based analytics and data warehousing to enable profound insights. The role may require the importing, cleaning, transforming, validating or modelling of data with the purpose of understanding or making conclusions from the data for decision-making purposes. Typically reports to the Chapter Lead.(107642) #VOIS Job Responsibility

  • Drives development and implementation of squad s analytics strategy and roadmap, incl. data source selection, data collection, transformation and standard reporting;
  • May extract, load or transform data from different sources either via scripting (e.g. SQL) or coding (e.g. Python);
  • May use predictive or descriptive analytics models;
  • Visualises and translates business requirements into concrete data engineering tasks;
  • Develops and deploys standard reports on squad KPIs and key operating metrics to enable continuous monitoring and improvement;
  • Develops smart and insightful dashboards and reports, tracking performance across channels to promote data-driven decision-making and optimize conversion;
  • Presents data in charts, graphs, tables, designing and developing relational databases for collecting data and building or designing data input or data collection screens;
  • Leads continuous, data-based improvement of activities via A/B testing and behavioural analysis;
  • Provides deep-dive analyses, generates insights and handles ad-hoc queries on a broad range of questions, (e.g. to define business strategies, specify product offerings, campaign performance, customer profiling, data quality investigations, testing);
  • May further build the data technology and systems landscape through integrating new data sources to the DWH or advancing existing tracking technology. Skills Data Modelling Data Visualisation Data Analytics and Insights Agile Business Acumen Coding Storytelling ,

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