Lulalend is a FinTech company with a belief in the power of small business. We work hard to empower businesses across South Africa with the funds they need to grow. Small business owners are the foundation for growth in our economy, and they deserve an easy and inspiring lending process.
Lulalend was founded because there is an underserved market for access to funding that the banks and other lenders overlook. We innovate in order to significantly reduce this credit gap - directly assisting our economy and job creation on a grand scale. So, by joining our team you're helping businesses stay open, grow and offer more job opportunities. Yay you!
Lulalend is a one of a kind business – literally. There is no-one in South Africa doing what we're doing yet, because we're awesome!
At Lulalend we:
- Are passionate about helping SMEs succeed
- Believe in responsible lending
- Strive to offer an unbeatable customer experience
- Value humility and teachability
- Embrace technology
- Communicate openly
- Work hard and play hard
Lulalend is South Africa's first and only online and automated business-lending platform aimed at providing small and medium businesses with quick access to funding to help them grow! We use data, technology and design to efficiently deliver capital to a market underserved by banks.
Our Lead Data Scientist role calls for an individual who champions the data science journey and has demonstrated an ability to lead and mentor junior team members. Not only will you need to be very strong technically applying a hands-on approach but you'll be passionate about helping others grow.
Working closely with our Head of Data Science, you will develop high-quality algorithms that produce scalable predictive models and help us make smarter decisions to deliver even better products.
In addition to applying data mining techniques and building high quality prediction systems integrated with our products you will act as a mentor and role model for the Data Scientists in our team.
Main responsibilities will include:
- Collaborate with our Product team to ensure data science work is prioritised across our team of Data Scientists so that quality delivery is ensured
- Develop, maintain and ensure utmost quality of our credit rating models and algorithms
- Monitor production runs to ensure accuracy and on-time delivery of model outputs and reports
- Work closely with the Data Engineering function to develop, maintain and scale the Data Warehouse
- Select features, build and optimise classifiers using machine learning techniques
- Provide input around how we can improve tools and processes already in place
- Identify new opportunities to improve customer performance and experience using machine learning methods
- Drive best practice around data collection, sharing knowledge and guidance with junior team members
- Data mining using state-of-the-art methods
- Extend company's data with third party sources of information when needed
- Enhance data collection procedures to include information that is relevant for building analytic systems
- Process, clean, and verify the integrity of data used for analysis
- Keep up to date with AI technology to help identify emerging trends and methodologies
- Participate in the recruitment process when we look to expand our team
THE COMPETENCIES WE'RE AFTER
- Strong team leadership skills
- Big picture thinker
- Excellent collaboration skills
- Hands-on mentality
- Influencing skills
- Strong problem-solver
- Focused on high quality output
THE SKILLS AND EXPERIENCE WE'RE LOOKING FOR
- Degree in a quantitative field (Mathematics, Computer Science, Engineering, Statistics or equivalent), preferably a Masters qualification
- 2+ years experience working as a Data Scientist within financial services
- 4+ years overall experience within data and analytics
- Proven track record of applying machine learning techniques and algorithms into production
- Experience motivating/mentoring other Data Scientists with the ability to get teams working together to resolve problems
- Leading by example, always demonstrating best practices around model development
- Understanding and appreciation of product development processes
- Great communication skills with the ability to relay technical information to a non-technical audience