- Role: Associate Data Scientist
- Duration: 4 – 6 months starting March 2020
- Location: Harare, Zimbabwe
This is an internship programme that can turn into a permanent position depending on performance and commitment during the programme.
A Data Scientist is responsible for identifying the insight opportunities present in the customer’s data and helping shape the data pipeline that deliver the insights by applying advanced analytics (e.g., machine learning) in collaboration with the customer. The Data Scientist is a technical, customer facing role, who along with the Big Data Engineer is accountable for the end-to-end data pipeline envisioning and development that starts with addressing issues of data acquisition and data sampling, data exploration and data quality assessment, data wrangling to massage the data so it is better suited to applying advanced analytics, and visualizing or reporting on such data to make the insights available to the customer’s business. The ideal candidate will have experience in customer facing roles and has a cross-disciplinary background consisting of statistics and software development. A technical BS degree in Computer Science or Math & Statistics background is highly desirable. At least one year of customer facing experience desired.
Advanced analytics, algorithm development, analysis services (tabular, multi- dimensional), backpropagation. bagging, boosting, Bayes, big data, business intelligence, classification, clustering, cloud data analytics, data architecting, data cleansing, data migration (cross platform / upgrade), data modeling (physical and logical), data movement, data potency, data transformation, data warehouse design, database architecture, database design, decision trees, descriptive analytics, forests, genetic programming, image processing, inverse deduction, machine learning, neural networks, predicative analytics, prescriptive analytics, recommendation, regression, rules, support vector machines, statistics, text mining.
Consultative requirements gathering, collaboration, stakeholder management, relationship management, technical oversight, technical recommendations, problem solving, risk management, architecture design session, program management, proof of concept design, technical demonstration.
TECHNOLOGIES & TOOLS
Azure Machine Learning Service, AWS Machine Learning, Azure Data Storage & Transformation Technologies, Hadoop, HBase, Hive, Hortonworks, Machine Learning, MapR, Microsoft R, ML, MongoDB, MariaDB, MySQL, NoSQL, Oracle, Oracle Exadata, Oracle SOA, Pig, Power BI, PostgreSQL, Python, QLik Tech, Revolution R, SAP HANA, SAS, Spark, SQL Server Analysis Services, SQL Server, SQL Server IaaS, SQL Server Integration Services, Sybase, Tableau, TSQL, TensorFlow, PyTorch, ScikitLearn.
PROGRAMMING & SCRIPTING LANGUAGES
R, Scala, Python, SQL, T- SQL, Java
NOTE: The technologies above are an idea of the tools you will be using and not necessarily a solid requirement. We will only accept applications that include a well structure resume with details of how you learnt and used any of the technologies and programming languages.
If you are interested in this position kindly send your CV to email@example.com with subject line of the position you are applying for.