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Junior Data Scientist Vacancy

by Alloyce N.
in Mzansi Jobs, Company Jobs In ZA
Reading Time: 3 mins read
0
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Table of Contents

  • Junior Data Scientist Vacancy
      • Job Classification
      • Job Family
      • Career Stream
      • Leadership Pipeline
      • Job Purpose
      • Job Responsibilities
      • People Specification
      • Preferred Qualification
      • Minimum Experience Level
      • Technical / Professional Knowledge
      • Behavioural Competencies

Junior Data Scientist Vacancy

Details
Location: Johannesburg, ZA
Date: 08-Nov-2022

Job Classification

  • REQ: 122375 – Refilwe Falatsi
  • Closing Date: 11 November 2022
  • Division: Nedbank Insurance
  • Functional Area: Corporate Actuarial
  • Employment Equity Statement: Preference will be given to individuals from underrepresented groups.

Job Family

Information Technology

Career Stream

Application Development

Leadership Pipeline

Manage Self Technical

Job Purpose

To design, prototype, and build next-generation analytic engines and services by applying strong expertise in matching learning , data mining and information retrieval .

Job Responsibilities

  • Develop statistical models and algorithms through the  use of libraries and abstractions
  • Conducts explority data analysis
  • Create value out of enterprise wide data
  • Provide insights to BI and BA to further exploit and present their models.
  • Apply advanced analytical techniques such as machine learning and artificial intelligence in order to derive business value.
  • Conduct data discovery for inclusion in models.
  • Keep abreast with latest tools and techniques.
  • Focus on specific date point within the data process life cycle.
  • Access and clean data and validate data quality.
  • Identify additional data sources.
  • Collaborates with model developers to implement and deploy scalable solutions.
  • Implement and maintain complex models and algorithms that drive innovation throughout the organization.
  • Ensure improvement of on-time performance and network planning,
  • Conduct self development through  researching best practices, conducting experiments, and collaborating with industry leaders.
  • Work with large data sets, simulation/ optimization and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, Gurobi, Arena, etc.)
  • Monitor and maintain models in production and re -train if necessary.
  • Support the achievement of the  business strategy, objectives and values.
  • Stay abreast of developments in field of expertise.
  • Ensure personal growth and enable effectiveness in performance of roles and responsibilities.
  • Contribute to the Nedbank Culture building initiatives (e.g. staff surveys etc.).
  • Participate and support corporate responsibility initiatives for the achievement of business strategy.
  • Seek opportunities to improve business processes, models and systems though agile thinking.

People Specification

Essential Qualifications – NQF Level
  • Matric / Grade 12 / National Senior Certificate
  • Advanced Diplomas/National 1st Degrees

Preferred Qualification

Degree Computer Science, Econometrics , Mathematical Statistics.

Minimum Experience Level

  • Degree in computer science, statistics, or operations research or related technical discipline.
  • 3 years’ experience in a statistical and/or data science role
  • Cursory knowledge of machine learning, statistics, optimization or related field
  • Experience with R, Python, Matlab is required, programming in C, C++, Java
  • Experience working with large data sets, simulation/ optimization and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, Gurobi, Arena, etc.)
  • Excellent written and verbal communication skills along with strong desire to work in cross functional teams
  • Attitude to thrive in a fun, agile start-up like environment.

Technical / Professional Knowledge

  • Data Mining
  • Data Tools
  • Data Warehousing

Behavioural Competencies

  • Planning and Organizing
  • Collaborating
  • Continuous Improvement
  • Innovation
  • Leveraging Feedback
  • Applied Learning

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