Senior Data Scientist - Cape Town
12 days ago
For this company data is a first class citizen and they have a lot of it. Their many different products generate all types of data, from your typical financial transactional data, to user activity data and even highly detailed system log or audit data.
The Data Science team seeks to find value out of all of this data, correlating events using multiple data sources. They look for reactive insights but more importantly find ways to predict activities before they have occurred sometimes in real time. These insights can be used to both protect customers as well as their business from harm. We work closely with Business and Technology by sharing insights through data visualization tools, which in turn guides strategy and increases our impact.
The successful Data Scientist will be responsible for seeking out data of any type, correlate it with other types of data to extract insights and value out of it. Supported closely by the DataOps Team you will research better ways to store, transform, aggregate and query data.
This team will analyse this data to obtain a better understanding of how our business is performing, utilize machine learning and AI to automate certain processes within the company using coding, statistical analysis, data analysis, visualization and modelling.
Familiarly required with statistical tests, distributions, maximum likelihood estimators, predictions, trends etc. This will also be the case for machine learning, but one of the more important aspects of your statistics knowledge will be understanding data analysis, conclusions and the experiments conducted.
Visualizing and communicating data findings is also incredibly important as well as making data-driven decisions. It will be important to be able to clearly communicate and describe your findings, both technical and non-technical. It can be immensely helpful to be familiar with data visualization tools like SSRS, GGPlot , Seaborn, PowerBI, Excel, Tableau, Kibana and Grafana to name a few.Ultimately, you should utilize data to provide suggestions on how to optimize any part of our value chain and in turn increase revenue or reduce operational costs.
Duties will include but not be limited to:
Statistical and Data analysis
Interact with Technology teams to understand sources of data, challenges around interpretation of data and providing guidance around the data we should log in our systems to maximize correlation and value.
Collaboration with product management and business leaders to understand current challenges and needs.
Collect data from external sources to enhance our understanding of the changes in our data trends.
Providing direction to the DataOps team around data needs, prioritizing sources and defining schema and performance requirements.
Investigate tools for transformation of data into usable formats depending on the use case, paying special attention to real-time vs batch data.
Research and Development of new data analysis technologies and validating their value within our environment.
Provisioning of Data Visualizations tools to clearly communicate findings and enable some self-service functionality where suited.
Provide easy to consume endpoints to enable other technology teams to consume data findings and utilize them in other systems.
Maintain documentation on all work conducted and a service catalogue of the service offered include SLA’s.
Predictive and classification models using supervised and unsupervised learning
Explain and breakdown complex mathematical/statistical concepts and correlate the effects thereof to real world scenarios in the business.
This job description is not intended to be an exhaustive list of responsibilities. The job holder may be required to complete any other reasonable duties in order to achieve business objectives.
5 Years proven experience as a Data Scientist
A graduate degree in a relevant discipline (Mathematics, Actuarial Science, Mathematical Statistics or similar )
A sound understanding of relational and non-relational databases
Experience in writing SQL, R, Python or related languages
Superior applied excel knowledge
Exposure to or interest in Big Data technologies or working with large datasets.
Experience in or exposure to analytical research/methodologies
Business interpretation of decision support data
Experience in ElasticSearch, Kafka, RabbitMQ, Apache Spark and other data pipeline tools.
Experience in Machine Learning tools not limited to Elastic Search ML and MS ML Server.
Experience in AI tools not limited to TensorFlow
Exposure to large data processing system design including storage, networking, CPU and GPU processing
Experience with deep learning/neural networks
Exposure to cloud technologies e.g. Azure, AWS
A postgraduate degree in a relevant discipline (Mathematics, Actuarial Science, Mathematical Statistics or similar )
Very strong maths and stats experience/skills
Strong client interaction skills
Experience in financial analysis
Planning & Organizing