Engenheiro de Dados Sênior
Sao Paulo, Sao Paulo, Brazil
há 1 dia

Qualification :

  • Post-grad in one of the following fields with strong academic credentials :
  • Computer Science / IT.
  • Operations Research / Applied Math.
  • Engineering.
  • Responsibility : Business :

    Business :

  • Works with the business team to identify the right business problem, gather the requirements and data required to answer the same.
  • Data exploration , hypothesis testing and statistical modeling are part of daily activities.
  • Involved in development , testing, evaluation and optimisation of models developed.
  • Analyzes data and generates insights that can be articulated to business stakeholders.
  • Develops hypothesis for testing in consultation with Principal / Domain SME and Business teams.
  • Stakeholder Management :

  • POC for all the daily based activities and ensures the availabilty of all the required information with all the team at all the times.
  • Build the collaterals which are durable and reusable
  • 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 :

  • Ensures that all the deliverables meets the delivery excellence standards and meets the stakeholders' expectations.
  • Identifies risks to project execution and works with stakeholders to mitigate the same.
  • 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 :

  • Perform exploratory data analysis and generate insights.
  • Validate hypothesis developed during exploration phase.
  • Present initial results to business stakeholders and identify the next steps.
  • Design experiments with test and validate multiple hypothesis to meet / exceed expectations of customer due to the dynamic environment.
  • 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 Market Basket Anaysis.
  • 5 Text Mining(Structured and Unstructured Data).
  • 6 NLP.
  • 7 Decision Trees.
  • 8 Network Analysis.
  • 9 Linear Programming.
  • 10 Optimisation.
  • 11 Deep Learning.
  • 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 avenues by disecting the data and identify which all models can be utilised for a given business problem.
  • Provide expertise thru PoCs and PoVs.
  • Knowledge Management :

    Prepare a design, requirement document.

  • 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.
  • People / Team Management :

  • Mentor a team of Associate Data Scientists.
  • Set the timelines and monitor the progress of the project.
  • Ensure the timely delivery of deliverables and addresses the concerns related to tasks.
  • Understand aspirations of team members.
  • Set goals for team members and monitor performance.
  • Manufacturing Oper-Manlog
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