TalentUp Africa uses quizzes and games, all based on specific lessons, to identify candidates’ capabilities, skill sets, and personalities. Through app-based games and quizzes, the selection process becomes quicker and more objective - time equals money, and selection of candidates will no longer be coloured by applicant’s, ethnicity, race, age, gender
Job Description
- In this role, you will work on large-scale data science/data analytics projects.
- Ability to lead effectively across organizations.
- You will Implement AWS services in a variety of distributed computing, enterprise environments.
- You will define system architectures and explore technical feasibility trade-offs.
- You will work on a code base with many contributors.
- You will be required to prototype and evaluate applications and interaction methodologies.
- You will be required to present complex technical information in a clear and concise manner to a variety of audiences therefore you will demonstrate written and verbal technical communication skills.
Your Profile
Qualification And Experience
- Bachelor’s degree, or equivalent experience, in Computer Science, Engineering, Mathematics or a related field
- 1+ years’ experience of Data platform implementation, including 1+ years of hands-on experience in implementation and performance tuning Kinesis/Kafka/Spark/Storm implementations.
- 3+ years experience developing cloud software services and an understanding of design for scalability, performance and reliability.
- 1+ years of IT platform implementation experience.
- Hands-on experience with Data Analytics technologies such as AWS, Hadoop, Spark, Spark SQL, MLib or Storm/Samza.
- Experience with one or more relevant tools (Flink, Spark, Sqoop, Flume, Kafka, Amazon Kinesis).
- Experience developing software code in one or more programming languages (Java, JavaScript, Python, etc).
- Proficiency with at least one of the languages such as C++, Java, Scala or Python.
- Experience with at least one of the modern distributed Machine Learning and Deep Learning frameworks such as TensorFlow, PyTorch, MxNet Caffe, and Keras.
- Experience with analytic solutions applied to the Marketing or Risk needs of enterprises
- Basic understanding of machine learning fundamentals.
- Ability to take Machine Learning models and implement them as part of data pipeline
- Experience building large-scale machine-learning infrastructure that have been successfully delivered to customers.
- Experience with AWS technology stack and current hands-on implementation experience required
Method of Application
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