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Data Scientist

3 months ago

Pretoria, Gauteng, South Africa Curiska (Pty) Ltd Full time

Minimum education (essential):

Bachelor's degree in Computer Science, Statistics, Mathematics, Actuarial Science or a related field.

Minimum education (desirable):

Honors or Masters degree Computer Science, Statistics, Mathematics, or a related field.

Minimum applicable experience (years):
5 years

Required nature of experience:

  • Proven experience in data analysis, statistical modeling, and machine learning.
  • Data cleaning, feature engineering, and model validation.
  • Data visualization tools (e.g., Tableau, Power BI Qliksense).

Skills and Knowledge (essential)**:

  • Proficiency in programming languages such as SQL, Python, R.
  • Data manipulation and analysis using SQL.
  • Big data processing frameworks like Hadoop or Spark.
  • Machine learning algorithms and techniques.
- statistical analysis and hypothesis testing.

  • Analyzing complex datasets, identify patterns, and extract meaningful insights.
- experimental design and A/B testing methodologies.

  • Validate large volumes of data.

Data Analysis and Modelling

  • Collect, clean, and preprocess data from various sources.
  • Develop predictive models and algorithms to solve complex business problems.
  • Perform model validation and finetuning to ensure accuracy and reliability.
  • Create visualizations and reports to communicate findings effectively.
  • Extract actionable insights from data analysis to support decisionmaking processes.
  • Collaborate with business stakeholders to identify key areas for improvement and optimization.
  • Provide datadriven recommendations for business strategies and initiatives.
  • Conduct adhoc analysis to answer specific business questions and solve problems.

Data Management and Governance

  • Ensure data quality and integrity throughout the data lifecycle.
  • Develop and implement data governance frameworks and best practices.
  • Collaborate with data engineers to optimize data pipelines and workflows.
  • Stay updated with the latest industry trends and advancements in data science.

Continuous Development and Improvement

  • Stay abreast of new techniques, algorithms, and tools in the field of data science.
  • Participate in conferences, workshops, and training programs to enhance skills and knowledge.
  • Share knowledge and expertise with team members through mentoring and coaching.