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Senior Data Scientist

Premium Job From Sage
Recruiter: Sage
Listed on: 5th November 2020
Location: Dublin
Salary/Rate: £Competitive
Salary Notes: £Competitive
Type: Permanent
Start Date: ASAP

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Data Science at Sage means giving businesses of all sizes the technology to better manage everything from money to people. As a Senior Data Scientist here, you'll be part of a global market leader but with a very local heart. Led by Glassdoor's top scoring UK CEO during the Covid-19 crisis, we're a FTSE 100 tech company with over 13,000 colleagues globally and we continually give back to our local communities.
Join us here in Dublin and you'll be working alongside a team of local tech specialists on the fantastic AutoEntry, one of the fastest growing automation software businesses on the market, which we acquired last year. It basically eliminates the pain point of data entry for accountants, saving huge amounts of time and effort and is now servicing over 150,000 businesses across the UK, US, Canada and Australia.
Its modern tech stack uses CI/CD; automated tests; internal package management; push-button deployments to all environments; separate staging environments, automatically provisioned per branch; PR and code review for all changes. In short, it is a pretty awesome piece of kit.
Ideal skills
The reason businesses all over the world rely on Sage: they trust us to continually innovate and improve. Our Data Scientists aren't just number-crunching machines. We look for radical thinkers who mine the depths of their genius to deliver amazing solutions to the most complex of problems. It's the kind of knowledge you'll have gained over a lengthy career ensconced in machine learning, programming Python and working with NumPy, Scipy, scikit-learn and pandas-ml. You'll need:

Strong theoretical foundations in linear algebra, probability theory and optimisation
An impressive ability to communicate projects comprehensively to non-technical audiences, not just technical ones
Familiarity with logistic regression, gradient descent, regularisation, cross-validation, overfitting, bias, variance, convex optimisation, SQL, sparse matrices and clustering - for starters!
To know when not to use machine learning as well as when to do so
Endless curiosity and a relentless drive to solve problems

Key responsibilities

Exploring all the angles from which problem domains can be approached to lead to a non-trivial, multi-model system that acts in unison to extract data from every document we receive
Playing a crucial part in building and scaling data capture globally within Sage - influencing its broader development within the company
Using machine learning to solve ideation and production problems, as well as working with machine learning infrastructure engineers to ship models
Writing production-quality code
Positioning yourself as a subject matter expert who demonstrates mastery and empowers internal stakeholders using the art of the possible

About Sage
Sage is a global company built on the unique personalities and characteristics of 13,000 colleagues across 24 countries. The market leader for cloud-based accounting, financial, enterprise management, people and payroll software, we empower the world's business heroes. Steve Hare has been recognised by colleagues as the top-scoring CEO on Glassdoor throughout the ongoing COVID-19 crisis, due to the high levels of communication and engagement throughout. As a worldwide FTSE 100 company, we do business the right way while giving back to our local communities. By giving each colleague five paid days a year to support the Sage Foundation, they can volunteer in whatever way they feel best. We believe in building a culture where colleagues feel they can bring their whole selves to work. Where people know they'll be judged on their performance and behaviours - not their identity. All qualified applicants will be considered for employment and not discriminated against based on their race, colour, age, religion, sexual orientation, gender identity, national origin or disability.