Main 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 internal Digital Strategic Framework. Responsible for the end-to-end data lifecycle – from strategic planning, data collection, through monitoring, evaluation, and incremental improvement.
- Reporting to: Chief Digital Officer
In this role, you will enhance the current and future analytic environment and data platforms, as well as associated, develop data products and services for consumption.
Further the purpose will include the identification of key organisational problem statements, opportunities, user data experience, and journey requirements, through data collection, and using a wide range of statistical, machine learning, and applied mathematical techniques to deliver insights and predictive analytics to decision-makers. In addition, you will provide technical advisory and support to senior data teams and decision-makers in municipalities within the domain of Marketing, communication, strategy, and Natural Language Processing
Specific Job 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
Outputs to be delivered
1) Data Pre-processing and Transformation
- 35%
- Demonstrate ability to transform raw data from multiple data sources. – Ability to understand the business requirements specification and use the suggested template to transform data.- Ability to understand the differences between data types and transform the data types when required.- Ability to write ETL jobs and automate pipelines when required.- Ability to investigative anomalies when loading data into the required data source- Ability to source external data sources to be used in machine learning processes.- Ability to work and know which platform tools to use for data transformation.- Exploring the data for patterns and trends,- Ability to translate and reproduce mockups design of data analytic dashboards
2) Modelling Building and Deployment
- 35%
- Demonstrate ability to translate business use cases into machine learning problems. Understand the end-to-end process of building a machine learning model including data transformations, train test split, saving and deploying machine learning models. Assist Senior Data Scientist to deploy machine learning models in production. Monitor and debug machine learning pipelines in production.- Ability to work and know which platform tools to use for machine learning and deployment.
3) Strategic support
- 15%
- Support senior managers and municipal communication teams to plan and execute agreed performance agreement goals for career development- Manage the team of data scientists to deliver all strategic and analytical outputs as required- Work with team members when required to execute data science team goals- Provide project support on domain-specific projects- Provide feedback to senior managers on work and deliverable progress- Write assessment reports to include the performance of algorithms used for machine learning use cases- identify data science innovation that creates propriety advantage for the company- Work with Senior data scientist to identify specific data science roles to specialize in the data science team- Proactively develop data products for emerging use-cases- Provide advisory and support to municipal data teams.
4) Behavioural Competencies
- 15%
- Demonstrate ability to develop and maintain personal and working relationships with others that aid in completion of work, information exchange and to foster and promotes optimal performance and overall organisational effectiveness- Demonstrate ability to research and document latest best practice applications of data science pipelines- Demonstrate ability to complete high-quality work without supervision- Demonstrate ability to work, adapt and contribute to changes in processes within the team
Responsibilities
- Support the chief digital officer and senior 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 modeling using internal data modelling platforms and tools
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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:
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Cloud:
- Microsoft Azure (must)
- AWS
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Google Cloud
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Big Data:
- Mondodb
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Hadoopo Cassandra
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Machine Learning:
- Kubeflow
- Tensorflow
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PyTorch
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Business Intelligence/Analytics and visualisation:
- Microsoft PowerBi (must)
- Microsoft Excel (must)
- Google Analytics (must)
- Adobe Analytics (must)
- Google Chartso NLTK (must)
- Textblobo SpaCy
- CoreNLP
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Datorama (advantage)
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Languages:
- Python (must)
- R (must)
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SQL (must)
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Conversational AI:
- Dialogflow
- Teneo
- Bot Framework / Bot Builder SDK (ideal)
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Watson Assistant
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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 trends and patterns 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 continuously deliver user-centric data visualisations, publications, and products
Skills / Abilities required to do the Job:
- Ability to develop machine learning tools built-in using python, R
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- Ability to manage both structured and unstructured data using SQL
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- Ability to visualise data using various tools- Ability to build conversational AI (artificial intelligence) models
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- Ability to model data for prediction
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- Ability to manage time and project deliverables
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- Ability to communicate with executives and senior management across sectors ( local government, government, and industry)
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- Basic understanding of marketing and communications management processes
Desired Skills:
- Python
- database technologies
- SQL
- artificial intelligence
- ETL
- –
- Sentiment Analysis
- – Stemming and Lemmatisation
- Keyword extraction
- Topic Modelling
- Text Mining
- Named Entity Recognition
- Machine learning
- Deep learning
- Programming
- Data Analysis
- Database configuration and management
- Data visualisation
- Predictive analytics
- Business Acumen
- Agile
Desired Work Experience:
- 2 to 5 years Data Analysis / Data Warehousing
Desired Qualification Level:
- Masters