Associate Data Scientist

4 weeks ago

Manila, National Capital Region, Philippines Cognizant Technology Solutions Full time

Not Applicable

Qualification:

Post-grad in one of the following fields with strong academic credentials:

  • • Computer Science/IT.
  • • Operations Research/Applied Math.
  • • Engineering.
  • • Statistics.

Responsibility:

Business:

  • 'Works with the business team to identify the right business objective and data required to answer the same.
  • Executes a data collection plan from both structured and unstructured sources that helps in data exploration , hypothesis testing and statistical modeling.
  • Analyzes data and generates insights that can articulated to business stakeholders.
  • Develops POCs that can be used to generate business decisions.
  • Simulates several scenarios through an interactive visualization that deepens the business understanding with underlying trends and root causes.

Stakeholder Management:

  • '
    • Communicate analytical results in a way that is meaningful for business stakeholders and provides actionable insights.
  • • Coordinates in communicating the data needs with both technology and business teams to ensure that right data is captured for analysis and modeling.

Project Management:

  • '
    • Ensure that the work goes ahead in a way that conforms to DS delivery framewrok and fulfills all outputs specifically outlined by stakeholders.
  • • Work with Business Operations and Delivering teams on designing, building and deploying data analysis systems for large data sets.
  • • Execute flawlessly on the DS project plan by adhering to timelines.
  • • Execute the design, analysis, or evaluation of assigned projects.

Data Analytics and Reporting:

  • '
    • Explore and examine data from multiple disparate sources.
  • Prepare a data collection plan from both structured and unstructured sources.
  • Collaborate and coordinate with Technology and Business teams for all data needs.
  • • Expert level proficiency in data handling (SQL).
  • Data Discovery & Profiling.

Data Discovery & Profiling:

  • '
    • Perform exploratory data analysis and generate insights.
  • Validate hypothesis developed during exploration phase.
  • Present initial results to business stakeholders and identify the next steps.

Data Modelling:

Create models using one or more of the platforms like R, SAS, Python, Matlab Model creation would involve one or more of the following technqiues:

  • 1 Classification.
  • 2 Clusterning.
  • 3 Time Series.
  • 4 Forecasting.
  • '
    • Testing and validating the model.
  • • Deriving insights and recommendations from the models.
  • • Performing data visualization and presentation to clients.

Innovation & Thought Leadership:

  • '
    • Provide thoughtleadership and dependable execution on diverse projects.
  • • implement best practices and technology.
  • • Discover new opportunities where advanced analytical techniques can be leveraged for solving business problems.

Knowledge Management:

  • Document all modeling steps in a systematic way including modeling process, insights generated , presentations , model validation results and checklists built in the project.
  • Prepare a one pager document that outlines and quantifies the business impact due to the DS project.

Must Have Skills

  • BigQuery
  • SQL Developer
  • Item Management

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