• Application Deadline:
• Position: Associate Data & ML Engineer


• Job Type Remote


• Qualification BA/BSc/HND


• Experience


• Location Lagos


• Job Field Data, Business Analysis and AI 
  

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