Anicalls | Jobs | Data Science Associate Manager | BigDataKB.com | 31-03-22

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Job Location: Bangalore/Bengaluru

  • Ability to work on 2-3 projects simultaneously, scope projects, realistically estimate work, and get customer agreement.
  • Apply appropriate statistical analysis and quantitative methods to analyze data and predict future trends and variability, especially in producing and maintaining reliable forecasts.
  • Contribute high-quality work as an individual contributor, in addition to management duties
  • Identify appropriate decision technology techniques to apply to relevant analytic frameworks.
  • Examples of decision technology tools that may be used include optimization, simulation, regression, decision trees, neural networks, cluster analysis, mixed models, etc.
  • Ability to balance accuracy of analysis with needs for rapid response.
  • Perform due diligence to ensure data is obtainable for the analysis required, and the analysis can be completed in the timeline requested.
  • Set up a model and conduct analyses using statistical, predictive or optimization tools.
  • Have a clear understanding of the uses and limitations of statistical applications.
  • Document steps, data sources. Ensure models are easily understandable and maintainable.
  • Drive the collection of new data and the refinement of existing data sources.
  • Possess a proven ability to develop partnerships with technical peers and business partners.
  • Lead project teams during all phases of the development life cycle, including requirements gathering and analysis, design, build, pilot, implementation, and continuous service
  • Lead functional teams to manage the end-to-end process: scope projects, build pipelines and datasets, synthesize results, craft automated dashboards/bots, and communicate an informed recommendation.
  • Manage budget, timeline, resources, and scope through prioritization throughout the course of all assigned projects
  • Lead a high-performing, high-throughput team of talented Data Scientists and business analysts, while driving the professional development goals of the team
  • Where relevant, clean, and structured data to facilitate analysis.

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