Data Scientist - Predictive Analytics & ML

Placements24; Mossel Bay; Hybrid; ZAR 700,000 - 1,100,000; Full time

Benefits offered by this job

Competitive salary

Health insurance

Retirement plan

Hybrid work arrangement

Professional development

Job summary

WhatJobs Direct is seeking a Data Scientist with a strong focus on predictive analytics and machine learning for a hybrid role in Mossel Bay, Western Cape, ZA. You will build and deploy ML models to uncover insights, forecast trends, and optimize business processes across domains.

The ideal candidate will have rigorous statistical modeling skills, hands-on ML experience, and the ability to translate complex data into actionable insights while collaborating with cross-functional teams in a

Qualifications

• Advanced degree in a quantitative field; research or industry ML work.
• Proven track record with predictive modeling projects.
• Proficiency in Python or R and ML libraries.
• Experience with SQL and data warehousing.

Responsibilities

• Develop and validate predictive ML models.
• Perform data exploration, cleaning, and feature engineering.
• Design and run A/B tests and experimental frameworks.
• Communicate findings to stakeholders with visualizations.
• Collaborate with engineering to deploy models into production.
• Monitor model performance and retrain as needed.
• Stay updated with advances in data science and ML.

Skills

Python

R

Machine Learning

SQL

Education

Masters/PhD in a quantitative field

Tools

scikit-learn

Pandas

TensorFlow

PyTorch

Job description

About the Role

WhatJobs Direct is seeking a talented Data Scientist with a strong focus on predictive analytics and machine learning to join our innovative team. This role, located in **Mossel Bay, Western Cape, ZA**, operates on a hybrid model, allowing for a flexible balance between remote work and in-office collaboration. You will be responsible for developing and deploying sophisticated machine learning models to uncover insights, predict future trends, and optimize business processes across various domains. The ideal candidate possesses a keen analytical mind, proficiency in statistical modeling, and hands-on experience with machine learning techniques. You will work with complex datasets, transforming raw data into actionable intelligence that drives strategic decision-making. Our client is committed to leveraging data science to solve challenging problems and create significant business value. This is an exciting opportunity to contribute to impactful projects and grow your career within a forward-thinking organization. We value creativity, curiosity, and a passion for data-driven solutions. The hybrid nature of this role is designed to offer both autonomy and the benefits of team synergy.

Key Responsibilities

• Develop, train, and validate predictive machine learning models using various statistical and ML techniques.
• Perform data exploration, cleaning, and feature engineering on large, complex datasets.
• Identify key business drivers and opportunities through data analysis and modeling.
• Design and implement A/B tests and other experimental frameworks to measure the impact of interventions.
• Communicate findings and insights clearly to both technical and non-technical stakeholders through visualizations and reports.
• Collaborate with engineering teams to deploy models into production environments.
• Monitor model performance and retrain or update models as necessary.
• Stay current with the latest advancements in data science, machine learning, and statistical modeling.
• Contribute to the development of data-driven strategies and best practices.

Requirements

• Master's or PhD degree in Statistics, Mathematics, Computer Science, Data Science, Economics, or a related quantitative field.
• Proven experience as a Data Scientist, with a strong portfolio of predictive modeling projects.
• Proficiency in programming languages such as Python or R, and relevant data science libraries (e.g., scikit-learn, pandas, NumSQL, TensorFlow, PyTorch).
• Expertise in statistical modeling, hypothesis testing, and experimental design.
• Experience with SQL and working with relational databases.
• Familiarity with big data technologies (e.g., Spark) and cloud platforms (AWS, Azure, GCP) is a plus.
• Strong analytical and problem-solving skills.
• Excellent communication and presentation skills, with the ability to explain complex concepts simply.
• Ability to work effectively in a hybrid work model, managing time efficiently between remote and office-based tasks.

Benefits

• Competitive salary and performance-related bonuses.
• Comprehensive health insurance and retirement savings plan.
• Generous annual leave and public holidays.
• Hybrid work arrangement offering flexibility.
• Opportunities for professional development, including courses and conferences.
• Exposure to diverse and challenging data science problems.
• Collaborative and innovative team environment.
• Modern office facilities and resources.