Apply strong software engineering & machine learning expertise to industrialise predictive & prescriptive solutions across big datasets and handle both streaming and non-streaming analytics use cases. Having deep understanding of analytics and data science, you will engineer performant and robust code and apply best in class development frameworks.
▪BSc/MSc in computer science, mathematics or related technical discipline
▪1-4 years’ experience in software engineering with exposure to statistical and/or data science role (5-10 years for Senior ML Engineer)
▪Deep knowledge and proven experience with optimizing machine learning model in a production context
▪Experience with Python or Scala is required. Background in programming in C, C++, Java is beneficial. Exposure to both streaming and non-streaming analytics Experience with SQL, Spark, Pandas, Numpy, SciPy, Statsmodels, Stan, pymc3, Caret, Scikit-learn, Keras, TensorFlow, Pytorch, Databricks is beneficial.
▪Experience working with large data sets, simulation/optimisation and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, Gurobi, Arena, etc.)
▪Refactor prototypes of predictive models into highly performant, production ready solutions
▪Work closely with Data Engineers and Data Scientists to create analytical variables, metrics, and models
▪Work closely with data scientists to solve difficult engineering and machine learning problems and produce high-quality code
▪Choose and use the right analytical libraries, programming languages, and frameworks for each task
▪Contribute to building client capabilitiesby coaching team members on data science methodologies and approaches
▪Contribute to best coding and engineering practice across AI projects
▪Build/refactor/develop code into reusable libraries, APIs, and tools
▪Able to build a sense of trust and rapport that creates a comfortable & effective workplace; collaborative
▪Attitude to thrive in a fun, fast-paced, startup-like environment
▪Open minded to new approaches and learning