Responsibilities

• Work with the Navikenz Data Scientist team to identify/implement the most appropriate techniques model selection and development for problems to be solved
• Build algorithms and design experiments to merge, manage, interrogate and extract data to supply tailored reports to colleagues, customers or the wider organization
• Test AI/ML models to select the most appropriate ones for use on a project
• Work with the team on data sourcing and/or developing data pipeline for the solutions
• Design/Build clear reports that tell compelling stories about the insights learned from data and the proposed actions/strategies/options as a result
• Assist the team on the model to make it scalable, maintainable and production-ready
• Stay up to date with the latest technology, techniques and methods
• Conduct research from which you’ll develop prototypes and proof of concepts
• Manage/maintain the repository of built ML models and monitor for opportunities to use built insights/datasets/code/models for other clients
• Prepare, maintain and present clear and coherent communication, both verbal and written, to understand data needs and report results
• Stay curious and enthusiastic about using algorithms to solve problems and enthuse others to see the benefit of your work

Qualifications/Experience

The ideal candidate will have a Bachelor’s, Master’s Degree in Statistics, Mathematics, Computer Science or another quantitative field, with around 3 years of professional experience manipulating data sets and building statistical models, and familiar with the following software/tools/techniques:

• Coding knowledge and experience with several languages: Python/R/Julia, Java/Javascript, REST, etc.
• Combined knowledge of computer science and applications, modeling, statistics, analytics and maths to solve problems
• Knowledge and experience in statistical, machine learning algorithms and techniques: Regression, Classification, Random Forest, Boosting, Decision Trees, text mining, social network analysis, neural networks, etc.
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Databricks, H2O.ai, etc.
• Experience visualizing/presenting data for stakeholders using: Matplotlib, ggplot, D3, etc.
• Good to have Experience with cloud based platforms/products – AWS, Azure, GCP, Kubeflow, AutoML etc.