Lead Data Scientist - Predictive Analytics

Placements24; Benoni; Hybrid; ZAR 1,000,000 - 1,600,000; Full time

Benefits offered by this job

Performance bonuses

Health insurance

Flexible working arrangements

Professional development

Cutting-edge computing resources

Hybrid work model

Job summary

Placements24 is seeking a Lead Data Scientist in Benoni, Gauteng to drive predictive analytics initiatives in a hybrid work environment. You will lead a team of data scientists through the full lifecycle, from data exploration to model deployment and monitoring.

The ideal candidate has a PhD or MSc, 7+ years of data science experience, strong leadership, and expertise in Python/R, ML frameworks, and cloud platforms. You will collaborate with business units to deliver impactful insights.

Qualifications

• Master's or Ph.D. in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
• Minimum of 7 years of experience in data science, with a significant focus on predictive modeling and machine learning.
• Proven experience leading data science projects and mentoring junior team members.
• Expertise in programming languages such as Python or R, and proficiency with relevant data science libraries (e.g., scikit-learn, TensorFlow, PyTorch, pandas).
• Strong knowledge of statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, time series analysis), and deep learning.
• Experience with big data technologies (e.g., Spark, Hadoop) and SQL databases.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation skills, with experience in a Hybrid work setting.

Responsibilities

• Lead the design, development, and deployment of predictive models using machine learning and statistical techniques.
• Oversee the entire data science workflow, including data acquisition, cleaning, feature engineering, model training, validation, and deployment.
• Mentor and guide a team of data scientists, providing technical leadership and fostering their professional growth.
• Collaborate with stakeholders across business units to understand their needs and translate them into data science projects.
• Identify new opportunities for leveraging data analytics to improve business outcomes and drive innovation.
• Develop and implement robust model monitoring and performance evaluation frameworks.
• Communicate complex analytical findings and recommendations clearly and effectively to both technical and non-technical audiences.
• Stay abreast of the latest advancements in data science, machine learning, and artificial intelligence.
• Contribute to the development of data governance and best practices within the organization. Ensure the ethical and responsible use of data and analytical models.

Skills

Leadership

Communication

Mentoring

Problem-solving

Analytical thinking

Education

Master's or PhD in Data Science / Statistics / CS / Mathematics

Tools

Python

R

scikit-learn

TensorFlow

PyTorch

Pandas

Spark

SQL

Job description

About the Role

Our client, a forward-thinking technology firm specializing in data-driven solutions, is seeking an accomplished Lead Data Scientist to drive their predictive analytics initiatives in Benoni, Gauteng. This role is instrumental in developing sophisticated models that forecast trends, identify opportunities, and mitigate risks across various business domains. You will lead a team of talented data scientists, guiding them through the entire data science lifecycle, from data exploration and feature engineering to model deployment and performance monitoring. This position offers a unique opportunity to work with vast datasets and cutting-edge technologies in a Hybrid work environment that combines the best of collaborative on-site work and focused remote productivity. We are looking for a visionary leader with a strong track record in predictive modeling and a passion for extracting actionable insights from complex data.

Key Responsibilities

• Lead the design, development, and deployment of predictive models using machine learning and statistical techniques.
• Oversee the entire data science workflow, including data acquisition, cleaning, feature engineering, model training, validation, and deployment.
• Mentor and guide a team of data scientists, providing technical leadership and fostering their professional growth.
• Collaborate with stakeholders across business units to understand their needs and translate them into data science projects.
• Identify new opportunities for leveraging data analytics to improve business outcomes and drive innovation.
• Develop and implement robust model monitoring and performance evaluation frameworks.
• Communicate complex analytical findings and recommendations clearly and effectively to both technical and non-technical audiences.
• Stay abreast of the latest advancements in data science, machine learning, and artificial intelligence.
• Contribute to the development of data governance and best practices within the organization. Ensure the ethical and responsible use of data and analytical models.

Requirements

• Master's or Ph.D. in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
• Minimum of 7 years of experience in data science, with a significant focus on predictive modeling and machine learning.
• Proven experience leading data science projects and mentoring junior team members.
• Expertise in programming languages such as Python or R, and proficiency with relevant data science libraries (e.g., scikit-learn, TensorFlow, PyTorch, pandas).
• Strong knowledge of statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, time series analysis), and deep learning.
• Experience with big data technologies (e.g., Spark, Hadoop) and SQL databases.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation skills, with experience in a Hybrid work setting.
• Ability to work effectively in a fast-paced, collaborative environment.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) is a plus.

Benefits

• Competitive salary package and performance bonuses.
• Comprehensive health, dental, and vision insurance.
• Generous paid time off and flexible working arrangements.
• Opportunities for professional development, including training, certifications, and conference attendance.
• Access to powerful computing resources and cutting-edge data science tools.
• A dynamic and innovative work environment.
• Career growth opportunities within a growing organization.
• Supportive team and leadership committed to work-life balance in a Hybrid model.