Senior Data Scientist

Micro Lending is an emerging business arena where the focus is on giving micro loan to Small Medium Enterprise (SME) Business owner; it aims to bring financial inclusion in a mass level as well contribute to the overall ecosystem of driving business and economies.

We seek passionate Senior Data Scientist who will take a key role on our team. The ideal candidate must apply advanced statistical and predictive modelling techniques to build, maintain, and improve on multiple real-time decision systems. Candidate must possess knowledge in engineering best practices, knowledge in discovering hidden information from vast amounts of data, be current on recent advances in machine learning.

• Conducts advanced data analysis and design complex algorithms.
• Identifies what data is available and relevant, including internal and external data sources, leveraging new data collection processes
• Leads discovery processes with stakeholders to identify the business requirements, designs experiments, test hypotheses, and build models to solve business problems. 
• Developing highly scalable machine learning models, operationalized the ML models, track model performance.
• Deploy, monitor, manage, and govern machine learning models in production.
• Handle machine learning operations and collaboration with data engineers, DevOps engineers, product managers, and technical partner teams.
• Understand data sources, conduct data discovery, apply complex techniques to produce features for automation using a hypothesis driven approach
• Partner with functional leads across the company to priorities areas of highest impact and be responsible for the delivery of these priorities
• Optimization machine learning products with professional software engineering skills
• Contribute to core advanced analytics and machine learning platforms and tools by research, discover new methodologies and new data feeds to support credit decisioning and other key business processes.
• Implementing leading edge academic research into pragmatic modeling solutions.

• At least 5 years of experience in the application of artificial intelligence, data mining, machine learning, or pattern recognition techniques to very large and diverse datasets.
• Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
• Strong coding capabilities in Python, Scala and their associated machine learning libraries.
• Deep skills in machine learning/data science, experience with deep learning
• Experience building and deploying machine learning solutions on Amazon Web Services (e.g. S3, EC2, EMR, Spark).
• Experience with Unix/Linux and AWS; Kubernetes a big plus
• Preferably familiar with data visualization techniques using one or more packages such as Tableau or D3 visualisation.
• Expert use of SQL, experience with non-relational databases is a plus
• Experience with ML Flow, Flask is a plus.
• Experience in Big Data technologies (Hadoop, Spark, Hive, Impala) is a plus
• Experience coaching junior machine learning engineers to improve their skills, and make them more effective, machine learning engineers.
• Experience in communicating with users, other technical teams, and senior management to collect requirements, describe machine learning product features, technical designs, and data product strategy.
• Experience in any of the following areas is a plus: credit risk management, financial analysis, marketing analytics, fraud detection, consumer analytic, computer vision