Machine Learning Engineer
4 weeks ago
Description
: Department
Data Science team
With our ever-growing data catalogue, the Data Science team helps to bridge the gap between data and the business, by providing the means to extract information from the data to be used in key decision-making processes.
The team is responsible for the identification needs for enhancing BAU tasks and processes, followed by the development and support of any model or tool delivered.
Position purpose
As a machine learning engineer, you have the opportunity to bring your experience into the team, improving the quality of work carried out by the team.
The role will require:
Building the team’s capability to deliver quality solution in a consistent and measurable way, Support the build, track, and maintenance of the full end-to-end lifecycle of studies and models, deliver the work through rigorous documentation, an interest in finding data patterns that can genuinely help the day-to-day tasks of any team, long term mindset, streamlining and automating repetitive tasks, help build and maintain the supporting infrastructure for the team, a keen eye to spot new opportunities or re-use of existing work.Main responsibilities
Experience and technical requirements
Essential requirements:
Experience with Python web development libraries (Dash, Django, Flask) and raw frontend development (JavaScript, HTML) Experience in pipelining and releasing solutions, with some focus on Data Science projects. Some C# and .Net Framework or, more generally, experience with object orientated programming. Experience in methods to access data (SQL, GraphQL, APIs) Experience in programming enterprise level applications (Test Driven Development, Docker) Knowledge of Azure cloud platform and its services Ability to identify and implement the best data science tool for the job, accompanied with a long-term support plan. Taking ownership of the deployment, and support of all the team’s solutions.Beneficial requirements:
Good theoretical understanding of the different data science tools and algorithms. Experience with data streaming and manipulation technologies (e.g., WebSockets, Kafka, Spark) Good mathematical and statistical background. Worked in energy trading sector or other experience in commodity trading. Other languages (e.g., French, or Italian)Person specification
Professional Forensic attention to detail Self-aware as to the value of current work vs. overall goal. Open minded Commercially minded – everything is a value proposition. Thrive when working in a high energy environment. Motivated by outcomes for users. Strong collaborator, both in person and online. A drive to create exceptional things.Hours of work:
40 hours per week - Monday to Friday – Hybrid
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