Senior Data Scientist

Lulalend; Cape Town; On-site; ZAR 900,000 - 1,200,000; Full time

Job summary

Lula in Cape Town, South Africa, seeks a Senior Data Scientist to turn data into decisions across product, operations, finance, marketing and credit. You will frame problems, build analyses and models, and deploy results for action.

You’ll own ML productionisation, monitor models in production, run experiments, build dashboards and raise data quality standards. Strong Python, SQL, and software engineering practices are essential; FinTech or lending interest is a plus.

Qualifications

• Degree in a numerical/quantitative field (math, stats, data science, CS, engineering, economics)
• 3-5 years in data science or advanced analytics
• Proven productionisation of ML models and monitoring in production
• Experience building/evaluating ML models on real-world data
• 3+ years using Python for data analysis (pandas, scikit-learn)
• 3+ years using SQL for data analysis
• Experience applying software engineering practices to data science (Git, code reviews, testing)
• Interest/experience in FinTech, lending, or small business environments

Responsibilities

• Partner with stakeholders to translate business questions into analytical problems
• Own productionisation of ML models with reproducible pipelines and deployment
• Monitor models for performance, drift, and data quality
• Build, validate and maintain predictive models (classification, regression, forecasting)
• Explore and analyze large datasets to uncover trends and opportunities
• Design and analyze experiments (A/B tests) and measure impact
• Build dashboards, reports and reusable analysis assets
• Raise data quality and best practices across the data team
• Contribute to data documentation and governance

Skills

Numerical degree

Data science experience

ML productionising

Python pandas

SQL querying

Software engineering practices

Education

Numerical or quantitative degree

Tools

Git

Docker

dbt

CI/CD (GitHub Actions)

Azure/AWS/GCP

Job description

ROLE PURPOSE

As a Senior Data Scientist at Lula, you will turn data into decisions across the business. You will work with teams in product, operations, finance, marketing and credit to frame problems, build analyses and models, and get the results into the hands of the people who act on them.

Your focus is practical data science with a strong machine learning edge: finding the signal, proving it with sound statistics, and making sure the models we rely on run reliably in production. You will work alongside our data and analytics engineers, set the standard for how data science is done at Lula, and help grow small and medium enterprises in South Africa through better use of data.

KEY RESPONSIBILITIES

• Partner with stakeholders to translate business questions into analytical problems, and communicate findings and recommendations clearly to technical and non-technical audiences.
• Own the productionisation of machine learning models, including reproducible pipelines, versioned code, automated testing and deployment, working with data engineers and analytics engineers.
• Monitor models in production for performance, drift and data quality, and drive retraining, remediation and improvement when they degrade.
• Build, validate and maintain predictive models (e.g. classification, regression, forecasting, segmentation).
• Explore, clean and analyse large datasets to uncover trends, drivers and opportunities.
• Design and analyse experiments (A/B tests, pilots) and measure the impact of business initiatives.
• Build dashboards, reports and reusable analysis assets that make insights self-serve.
• Help raise the standard for how data science is done at Lula
• Contribute to data quality, documentation and good practice across the data team.

THE SKILLS AND EXPERIENCE WE’RE LOOKING FOR

• A numerical or quantitative degree (e.g. mathematics, statistics, data science, computer science, engineering, economics, finance)
• 3-5 years' experience in a data science or advanced analytics role
• Proven experience productionising machine learning models and monitoring them once live (performance, drift, data quality)
• Experience building and evaluating machine learning models on real-world data
• At least 3 years' experience actively using Python in data analysis or modelling (pandas, scikit-learn or similar)
• At least 3 years' experience actively using SQL for data analysis
• Experience applying software engineering practices to data science work (Git, code review, automated testing)
• Experience in FinTech, lending or small business environments, or a strong interest in the space

Advantageous

• Familiarity with MLOps tooling such as MLflow, DVC or similar (experiment tracking, model registry, monitoring)
• Experience with dbt and CI/CD (e.g. GitHub Actions)
• Exposure to cloud data platforms (Azure, AWS or GCP) and cloud data warehouses (e.g. Snowflake)
• Experience with notebooks and collaborative analytics tools (e.g. Hex)
• Exposure to Docker, workflow orchestration or infrastructure as code
• Experience mentoring or technically guiding other data professionals

OUR TECH STACK

• Azure (Functions, databases, blob storage)
• DBT
• Snowflake
• Airflow
• Airbyte
• Event Grid