‍08 / 11 / 2018

Senior Data Scientist

Job Overview

As a data scientist, you will be required to develop robust privacy and risk management software, by implementing and evaluating prototypes and algorithms for anonymity, encryption and risk assessment. You will also contribute to building predictive analytics and machine learning applications for Trūata customers using their anonymized data. You will be a member of a highly skilled cross-disciplinary technical team designing and building a platform to enable enterprises to perform analytics on their customer data in a GDPR-compliant way. This position reports into Trūata’s Chief Data Scientist.

Key Responsibilities

  • Core research on critical topics relating to anonymity, encryption, privacy and risk management, i.e. differential privacy, homomorphic encryption, etc.
  • Understand business objectives and customer requirements
  • Development of quantitative methods for measuring privacy vs analytic utility
  • Development of techniques for privacy-enhanced handling of outliers
  • Development of literature reviews / market landscape reports
  • Development of algorithms to implement required privacy enhancement controls
  • Ongoing evaluation of data privacy controls for each customer, identification of area for concern
  • Development of sample data for testing and evaluation
  • Development of machine learning and predictive analytics models using anonymized customer data to support their key business requirements
  • Large-scale evaluation of effectiveness of Trūata anonymization techniques and machine learning models developed for customers
  • Publication of selected results in relevant conference proceedings or journals
  • Creation of patent descriptions and applications to cover any IP created

Minimum requirements

  • Post-graduate degree (PhD preferred) in a technical discipline (computer science, statistics, engineering)
  • Evidence of advancing a technical field of research (via published work, live use case results, etc)
  • Strong (5+ years) skills in related programming environment (Python/Jupyter, Scala/Spark, R, etc)
  • Excellent analytical and statistical analysis skills
  • Excellent skills in manipulating and analyzing data using dataframes, pivot tables, visualization tools
  • Experience working with and creating data architectures
  • Practical experience using machine learning and analysis techniques (clustering, regression, decision tree learning, artificial neural networks, etc) and their real-world advantages, drawbacks and ideal usage scenarios
  • Direct industrial experience (1 year+) of understanding business requirements, applying data science concepts, implementing prototypes and applying scientific methodology to evaluating results and optimisation
  • Ability to present technical concepts and results clearly to different business functions and stakeholders


  • Strong SQL skills
  • Good working knowledge of Big Data technologies including Spark, Hadoop, Cassandra, Kafka, Redis, Hive, Impala
  • Experience with cloud infrastructure providers (AWS/Azure)
  • Excellent experience with data partitions and transformation, and in-memory computations (large-scale join / groupby / aggregations)
  • Experience designing and building large scale Spark applications and data pipelines, monitoring and optimizing Spark job performance
  • Industry experience in relevant vertical such as financial services, travel / hospitality, telecom, insurance, health
  • Experience in data privacy, GDPR compliance and risk management
  • Strong Javascript skills

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