Data Scientist

Listing reference: track_000498
Listing status: Closed
Apply by: 13 May 2021
Position summary
Industry: Telecommunication Services
Job category: IT and Telecommunications
Location: Centurion
Contract: Permanent
EE position: Yes
Introduction
Tracker requires the services of a Data Scientist in our Technology Department. The Data Scientist will be responsible for design, analyse, develop and deliver sophisticated data science and machine learning solutions, results and products in a telemetry/telematics engineering environment by utilising relevant experience with mobile/accelerometer signal and data processing, along with strong mathematical, systems engineering and/or computer scientific skillsets. Should you be interested in this challenge and meet the job requirements, please forward your application before the closing date.
Job description

  • Deliver data science and related projects on time, in budget, with the desired functionality, at the defined quality level in a sustainable way.
  • Develop innovative and sophisticated but sustainable and producible ML/Data Scientific solutions based on telemetry data/telematics data/mobile data/other sensor data sources.
  • Meet best practice criteria in the testing of software.
  • Complete work orders in appropriate timescales.
  • Maintain and systems without introducing new defects.
  • Enhance systems to support and move to new technologies.
  • Share knowledge with development and support teams.
  • Document systems, including enhancements to facilitate knowledge sharing.
  • Ensure that the approved best practice development processes and standards are followed.
  • Effective use of development toolset.
  • Follow department development standards.

Minimum requirements

  • BEng/BSc (4 years) (completed) or BEng/BSc Honours (Completed) or Meng/MBSc (completed or in progress) or
  • Strong preference for Engineering degree with relevant software, systems and data research/development focus/exposure
  • Electronic / Electrical or Computer or Systems or related Engineering.
  • Computer Science, in combination with strong Statistical, Mathematical and Applications Development
  • First-hand experience in Engineering Research projects and/or Data Scientific Research projects with a strong focus on Engineering research for purposes of implementation.
  • Minimum exposure to 1 project where full responsibility for all work, from data gathering from raw source (preferably sensor based raw data), to analysis design, to machine learning/optimisation/statistical approach, to final results, culminating in (formal or informal) publication of results.
  • Demonstrate proficiency with university level Engineering mathematics
  • Demonstrate proficiency with university level statistics
  • Demonstrate proficiency with either R/MatLab or Python SciKitLearn MathLibs StatsLibs.
  • Minimum last 2 years C/C /Java/Python development experience
  • Minimum 4 years direct hands-on software development experience in an Engineering and/or Software Development environment.
  • Minimum 1 project direct hands on experience in Telematics/IoT/Telemetry related industry.
  • Minimum 4 years working experience in the following technologies:
  • Advanced Linux
  • MatLab and/or R
  • Python
  • C# or C or Objective-C or C
  • Java or Scala
  • SQL
  • Hadoop (or MS Azure versions)
  • Spark and/or Yarn (or MS Azure versions)
  • Analysis research execution, analysis, delivery of results.
  • Experience with concepts such as Quaternions, Adaptive Low Pass Filters, FFT, Linear Algebra, Advanced Calculus, Pattern Detection Approaches, Moments Analyses, etc.
  • Application of statistical hypothesis testing, distribution matching, etc.
  • Exposure to concepts such as hyper-parameter optimisation, multi-model comparison, etc.
  • Sufficient exposure to Best Practice Software Engineering experience important (version control e.g. Git, test cases, etc.)
  • Comfortable database and data centric work experience of relevance.
  • Exposure to any Cloud technologies an advantage.
  • Self-starter
  • Ensures high quality.  
  • Encourages collaboration and delivering within the delivery processes. 
  • Continuous self-learning
  • Able to work effectively on own.
  • Able to work effectively within a team.
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