Senior Data Scientist

Datonomy Solutions; Johannesburg; On-site; ZAR 800 000 - 1 200 000; Full time

Job summary

A leading data solutions firm is seeking a Senior Data Scientist to develop and operationalize advanced machine learning models for retail analytics. You will work on customer segmentation, demand forecasting, and deploy AI tools to improve business outcomes. Candidates should have strong programming skills in Python and experience in a data science role. A master's degree in a related field and proficiency in SQL and data visualization tools are required. This position is based in Johannesburg, Gauteng.

Qualifications

• Strong programming skills in Python including libraries like Pandas and NumPy.
• Experience with SQL and data pipeline operations in cloud environments.
• Proficiency in data visualization tools like Power BI or Tableau.

Responsibilities

• Design, develop, and deploy machine learning models for retail use cases.
• Conduct feature engineering and model validation for accuracy.
• Collaborate with business stakeholders to integrate analytical outputs.

Skills

Python programming skills

Experience with SQL

Data visualization tools

Machine learning algorithms knowledge

Communication skills

Education

MSc in Data Science or related field

Tools

Pandas

NumPy

Scikit-learn

TensorFlow

Power BI

Tableau

Job description

Cape Town based candidates only.

Job Overview

The Senior Data Scientist will be responsible for developing, validating, and operationalizing advanced machine learning and AI models that support strategic business outcomes across the retail value chain including customer segmentation, demand forecasting, price optimization, and recommendation systems. The role requires a combination of strong technical expertise, business acumen, and leadership skills, with the ability to translate analytical outcomes into actionable business strategies for diverse stakeholders.

Key Responsibilities

• Data Science & Modelling: Design, develop, and deploy machine learning models for key retail use cases such as customer segmentation, churn prediction, product affinity, and demand forecasting.
• Apply unsupervised and supervised learning techniques (e.g., clustering, regression, decision trees, ensemble methods, NLP, deep learning) to large‑scale structured and unstructured datasets.
• Build and maintain predictive models and experimentation frameworks to improve forecast accuracy and optimize marketing, pricing, and inventory decisions.
• Conduct feature engineering, model validation, and performance tuning to ensure accuracy, interpretability, and scalability.
• Integrate LLMs and generative AI tools where relevant to enhance analytics, reporting, and customer‑facing automation (e.g., chatbots, product search).
• Partner with key business stakeholders (Marketing, Supply Chain, Merchandising, Finance) to translate analytical outputs into strategic recommendations.
• Lead the creation of customer and product segmentation frameworks that drive targeted campaigns, loyalty engagement, and personalized promotions.
• Collaborate with cross‑functional data teams (Engineering, BI, Cloud) to ensure data availability, integrity, and governance.
• Support data storytelling and insight visualization through dashboards, visual models, and presentations to non‑technical audiences.
• Define and implement model validation, bias detection, and guardrail testing to ensure AI model reliability, fairness, and brand alignment.
• Drive continuous improvement in model performance through automation, monitoring, and A/B testing.
• Establish documentation and version control standards across ML pipelines for transparency and reproducibility.
• Mentor junior Data Scientists and Analysts, fostering a culture of experimentation and innovation.
• Contribute to the development of ML Ops standards, CI/CD pipelines, and deployment automation within the data science environment.
• Collaborate with external vendors and research partners to evaluate new techniques and tools.

Required Skills & Experience

• Strong programming skills in Python (Pandas, NumPy, Scikit‑learn, TensorFlow, PyTorch, Statsmodels).
• Experience with SQL and working knowledge of data pipelines and cloud environments (AWS / Azure / GCP).
• Proficiency in data visualization tools (Power BI, Tableau, Matplotlib, Seaborn).
• Solid understanding of machine learning algorithms, statistical modeling, and time‑series forecasting.
• Exposure to LLM validation, prompt engineering, and RAG frameworks will be highly advantageous.
• Prior experience applying data science within retail, e‑commerce, FMCG, or financial services preferred.
• Proven ability to translate analytical findings into business value (customer retention, campaign optimization, operational efficiency).
• Strong communication skills and comfort engaging senior business stakeholders.

Qualifications

• MSc or equivalent in Data Science, Computer Science, Artificial Intelligence, or Applied Mathematics.
• (advantageous) years experience in a data science or ML engineering role, preferably within large‑scale data environments.