PURPOSE
Data Scientist will be responsible for the application of data science and advanced quantitative methods, which include machine learning, deep learning, artificial intelligence, predictive analytics to enable key strategic, tactical, and operational use-cases within the domain of marketing, communications, strategy, and Natural Language Processing – as per the Digital Strategic Framework. Responsible for the end-to-end data Lifecyle – from strategic planning, data collection, through monitoring, evaluation, and incremental improvement.
KEY WORK OUTPUT AND ACCOUNTABILITIES
- Support the chief digital officer and snr data architect using a variety of state-of-the-art cloud based technologies to solve data analysis and prediction problems.
- Identify and act on new opportunities for data driven business in data science and analytics.
- Recognise when existing solutions can be generalised to solve new problems and address new data-as-a-service verticals
- Work in a collaborative environment developing data science methods, tools, and algorithms to solve problems.
- Become fluent in analytical modelling using the client’s internal data modelling platforms and tool;
- Continuously learn and apply latest and fit-for-purpose, open-source and proprietary tools and technologies to achieve results, including some or all of the following:
Cloud
- Microsoft Azure (must)
- AWS
- Google Cloud
Big Data
- Mondodb
- Hadoop
- Cassandra
Machine Learning
- Kubeflow
- Tensorflow
- PyTorch
Business Intelligence/Analytics and visualisation
- Microsoft PowerBi (must)
- Microsoft Excel (must)
- Google Analytics (must)
- Adobe Analytics (must)
- Google Charts
- NLTK (must)
- Textblob
- SpaCy
- CoreNLP
- Datorama (advantage)
Languages
- Python (must)
- R (must)
- SQL (must)
Conversational AI
- Dialogflow
- Teneo
- Bot Framework / Bot Builder SDK (ideal)
- Watson Assistant
- Associated tools and technologies as they become available, and the platform evolves
- Load and merge data originating from diverse sources.
- Performa data cleansing, and quality management.
- Pre-process and Transform data for model building and analysis.
- Troubleshoot data quality issues and work with team members to reach solutions
- Perform descriptive analytics to discover trend and pattern in the data;
- Create visualizations, including dashboards to provide insights on large data sets and input to finished reports
- Develop predictive models for business solutions.
- Deploy predictive and other models to production.
- Build and train NLP models
- Analyse output products to assure data quality and conformance to requirements.
- Develop technical specification for 3rd party platform data integration and streaming
- Participate in continuous improvement efforts to increase available data quality and speed of delivery
- Address ad-hoc domain-specific data analytic requirements from domain or cluster leaders; and a continuously deliver user-centric data visualisations, publications, and products
KNOWLEDGE REQUIRED TO DO THE JOB:
- ETL
- Sentiment Analysis
- Stemming and Lemmatisation
- Keyword extraction
- Topic Modelling
- Text Mining
- Named Entity Recognition
- Machine learning
- Deep learning
- Programming
- Data Modelling
- Database configuration and management
- Data visualisation
- Data analysis
- Predictive analytics
- Agile
- Exposure to financial services and/or fast retail/FMCG
- Business acumen
SKILLS / ABILITIES REQUIRED TO DO THE JOB:
- Ability to develop machine learning tools built in using python, R
- Ability to manage both structured and unstructured data using SQL
- Ability to visualise data using various tools
- Ability to build conversational AI (artificial intelligence) models
- Ability to model data for prediction
- Ability to manage time and project deliverables
- Ability to communicate with executives and senior management across sectors (local government, government, and industry)
- Basic understanding of marketing and communications management processes
PERSONAL ATTRIBUTES REQUIRED FOR THIS JOB:
- Project Management
- Problem solving and analytical
- Diligence
- Good business judgment
- Incumbent to be result and self-driven
- Good communication skills
- Self-direction and eagerness to learn
- Independent worker
- Strong time-management skills
- The ability to work on multiple projects for multiple stakeholders
- The ability work and deliver under pressure
- The ability to build internal and external relationships
- The ability to solve problems.
- The ability to rotate around a problem, to see if solutions can be gained in different ways.
- The ability to work in an ever changing, unstructured environment.
- The ability to learn new data tools and technologies speedily and deploy
- The ability to work as part of a team, with vastly differing skill sets and opinions.
- The ability to contribute ideas to the quorum.
- A systems approach to thinking, as opposed to a siloed approach. The candidate needs to understand how their work affects the greater system.
- The ability to work without supervision and take accountability for the work they deliver.
- The ability to liaise with a client, sifting through the fluff and extracting the actual requirements
MINIMUM REQUIREMENTS:
- Bachelor’s or Honour’s degree in Statistics, Mathematics, Applied Mathematics, Physics , Econometrics, Actuarial Science or equivalent experience
- Masters in Statistics, Mathematics, Applied Mathematics, Physics, Econometrics, an advantage
- 3+ years data science and analysis experience
- Proficient in Python and database technologies
Please note that should we not contact you within two weeks please consider your application unsuccessful.
Desired Skills:
- Data Science
Desired Work Experience:
- 2 to 5 years
Desired Qualification Level:
- Degree