Great opportunity for a DATA SCIENTIST (with Python or C++) to join a leading company delivering SaaS ARTIFICIAL INTELLIGENCE (AI) CONSUMER BEHAVIOUR INSIGHT to the RETAIL & FINANCIAL SERVICES Sectors.
Based in SANDTON this DATA SCIENCE position offers a salary of R650K – R700K/annum.
This technology ANALYTICS/DATA SCIENCE company is a Global industry-leader in MACHINE LEARNING, ARTIFICIAL INTELLIGENCE, DATA AUTOMATION and IN PREDICTING CONSUMER BEHAVIOUR for the RETAIL and FINANCIAL SECTORS. Using AI they predict consumer behaviour which helps their clients maximise efficiency and customer satisfaction.
Their core strength & SaaS Product provides an ability to match people with products, match inventory with business opportunity, match prices with spending propensity, and match people with usage patterns, through the use of DEEP LEARNING ALGORITHMS.
The Data Science team have been building AI models to predict consumer behaviour for over a decade - they are the leaders in AI platforms that deliver AUTOMATED CONSUMER BEHAVIOUR PREDICTIONS using PetaBytes of data, to inform actionable insights.
As DATA SCIENTIST you’ll join the team delivering automated consumer behaviour prediction products, with results that are far better than traditional statistical or Machine Learning methods. You will help automate and commoditise cutting edge AI results. Beyond automation of the data science process, another focus will be to make sure you stay ahead of the pack in terms of accuracy, speed, and scalability by being creative and diligent. You’ll join a team improving automated feature selection, audit automated pre-processing, improve automated, Deep Net Architecture and meta param optimization. Also keep abreast of latest breakthrough ML publications and suggest adoption where relevant.
Experience building deep nets using Python or C++.
Experience working on datasets larger than 1 TB.
Proficiency in using Recurrent Neural Networks architecture.
Proficiency in using NumPy, SciKit, TensorFlow.
Experience in distributed Deep Net implementations such as a Spark TensorFlow integration.
Experience in writing lambda functions will be preferred.
Strong University level Math, Physics, Applied Math or Mathematical Statistics background required.
If you qualify for this role, please email your CV directly to:
021 801 5001
If you have not had a response to your application within 14 days please consider your application to be unsuccessful.