Senior Data Specialist at Workforce Africa

PRIMARY RESPONSIBILITIES:
The incumbent will be responsible for:

• Selecting features, building and optimizing classifiers using machine learning techniques
• Data mining using state-of-the-art methods
• Extending company’s data with third party sources of information when needed
• Enhancing data collection procedures to include information that is relevant for building analytic systems
• Processing, cleansing, and verifying the integrity of data used for analysis
• Doing ad-hoc analysis and presenting results in a clear manner
• Creating automated anomaly detection systems and constant tracking of its performance
• Developing robust analytical models to address complex business problems and driving innovation

Qualification

• Bachelor’s degree (or higher) in computer science, math, software engineering, statistics, data science or a related technical field.

Knowledge

• 5 yrs experience with programming languages like SQL, Python, and R
• Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
• Familiarity with business intelligence tools (e.g., Tableau)
• Strong mathematics skills (e.g., statistics, algebra)
• Experience with big data technologies such as Hadoop and Spark
• Good applied statistics skills, such as distributions, statistical testing, regression, etc. . . . . Thorough understanding of Data-Science concepts and strong ‘hands-on’ expertise in architecting AI/ML solutions for challenging use-cases and in building classical and Deep Learning models.
• Specialization in one of the Data-Science areas like NLP/NLU, Time-Series Modelling, Graph Mining or Computer Vision
• Exceptional technical writing skills
• Ability to communicate complex data in a simple, actionable way
• Ability to visualize data in the most effective way possible for a given project or study
• Familiarity with data management tools
• Ability to work independently and with team members from different backgrounds
• Excellent attention to detail