Data Scientist

JVR Software; Johannesburg; On-site; ZAR 600,000 - 900,000; Full time

Job summary

JVR Software in Johannesburg seeks a data scientist to translate complex business problems into analytical solutions, build predictive models, and communicate insights to stakeholders. The role requires strong Python for data analysis and model development, solid SQL experience, and proficiency in statistics and EDA.

You will work with large datasets, perform feature engineering and model optimization, and validate models in an Agile environment using cloud platforms and version control.

Qualifications

• Relevant degree in quantitative field (Data Science, Statistics, Mathematics, Actuarial Science, CS, or Engineering).
• Strong data science experience with Python for data analysis and model development.
• Strong SQL experience for data wrangling and querying.
• Solid understanding of statistics, probability, and hypothesis testing.
• Experience with exploratory data analysis (EDA) and data preparation.
• Experience building and evaluating machine learning models and forecasting techniques.
• Experience with feature engineering and model optimization.
• Experience working with large and complex datasets.
• Experience with Scikit-learn and related machine learning libraries.
• Experience creating data visualizations and presenting insights to stakeholders.
• Experience translating business requirements into analytical solutions.
• Understanding of model validation and performance measurement techniques.
• Experience working in cloud environments such as Azure, AWS, or Google Cloud Platform.
• Experience with Git and version control systems.
• Strong analytical, problem-solving, and communication skills.
• Agile / Scrum experience.
• Passion for data, analytics, and continuous learning.

Skills

Data Science

Python

SQL

Statistics

EDA

Machine learning

Forecasting

Feature engineering

Big data

Scikit-learn

Data visualization

Business requirements translation

Agile/Scrum

Cloud platforms

Git

Education

Relevant quantitative degree (Data Science/Statistics/Mathematics/Actuarial Science/CS/Engineering)

Tools

Scikit-learn

TensorFlow/PyTorch

Databricks

Apache Spark

Azure ML

SageMaker

Vertex AI

R

Power BI/Tableau/Looker

Git

Job description

Requirements:

• Relevant Degree in Data Science, Statistics, Mathematics, Actuarial Science, Computer Science, Engineering, or a related quantitative field
• Strong Data Science experience
• Strong Python experience for data analysis and model development
• Strong SQL experience
• Strong understanding of statistics, probability, and hypothesis testing
• Experience with exploratory data analysis (EDA) and data preparation
• Experience building and evaluating machine learning models
• Experience with predictive analytics, classification, regression, clustering, and forecasting techniques
• Experience with feature engineering and model optimization
• Experience working with large and complex datasets
• Experience with Scikit-learn and related machine learning libraries
• Experience creating data visualizations and presenting insights to stakeholders
• Experience translating business requirements into analytical solutions
• Understanding of model validation and performance measurement techniques
• Experience working in cloud environments such as Azure, AWS, or Google Cloud Platform
• Experience with Git and version control systems
• Strong analytical, problem-solving, and communication skills
• Agile / Scrum experience
• Passion for data, analytics, and continuous learning

Advantageous:

• Experience with TensorFlow or PyTorch
• Experience with Natural Language Processing (NLP)
• Experience with Time Series Analysis and Forecasting
• Experience with Deep Learning models
• Experience with Power BI, Tableau, or Looker
• Experience with Databricks or Apache Spark
• Experience with Azure Machine Learning, AWS SageMaker, or Vertex AI
• Experience with R programming language
• Experience within Financial Services, Insurance, Telecommunications, Healthcare, or Retail environments
• Experience conducting research-driven analytics projects