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Machine Learning & Data Science at Moneycast

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  • London
  • fulltime
  • -
  • We’re a London based fintech start up, building a B2B payments platform. We are helping to empower small businesses by giving them control of their payments and cash flow, getting them better trade terms, guaranteed savings and ensuring they never go unpaid. Our short-term opportunity is a simple accounts receivable and payable tool for small businesses. The mid-term opportunity is a trade network connecting the near £1trillion annual spend of small businesses.

    We are looking for a Machine Learning & Data Science Expert to help us build out our ML & data science capability and to drive new innovative features which will help us to grow and build greater experiences for our customers.

    This is an ideal opportunity for an experienced Senior ML Engineer that wants to take their next step towards leading the development of cutting edge applications of Machine Learning, in a venture backed start-up.

    We would preferably like someone who is able to join us in our London Old Street office on Tuesdays and Thursdays.

    Responsibilities:

    • Lead on the development of the in-house capabilities and infrastructure required to deliver rapid data/ML prototypes and proof-of-concepts, as well as the implementation of productionised pipelines and environments for user-facing production ML-based capabilities and features
    • Work with stakeholders and the project team to identify and scope out ML, AI and data science opportunities, feeding into the product roadmap, helping with the specification of related requirements, NFRs and KPIs
    • Assist the product team with the creation of experience flows, exploring use cases, behaviours, and user experiences needed to deliver new innovative features
    • Communicate opportunities, approaches, implementation challenges, risks etc to technical and non-technical audiences
    • Act as a technical expert and leader within the data domain, upskilling, mentoring and coaching other engineers in ML techniques, approaches and implementation, ensuring that solutions are operationally supportable (MLOps)
    • Assist and advise in the seamless integration of ML solutions into the existing serverless technology stack - AWS, Lamba, Node.js

    Requirements

    • A degree, Master's or PhD in a quantitative or computational discipline
    • 5+ years of professional data science and machine learning experience, working on computation statistics,
    • Significant demonstrable experience developing and deploying data science and ML capabilities in production settings, you understand the potential pitfalls with implementing data pipelines and can call on real-world wisdom to identify risks before they impact delivery
    • Able to demonstrate experience taking the lead on complex data solutions that have resulted in real customer value
    • Proven experience working with large, complex sets, ideally within a fintech context
    • A strong growth mindset - promotes experimentation, engaging in and learning from processes and capitalising on setbacks to move forward
    • Has a consistent work ethic, shows a bias to action and a hunger for achieving results
    • A continuous thirst for learning and desire to improve yourself, the team and product
    • Demonstrates excellent communication skills and is comfortable communicating with colleagues at all levels
    • Ability to work collaboratively in cross-functional teams

    Benefits

    • Competitive Compensation
    • Flexible Working Hours
    • Work From Home 3 days a week
    • Work From Home Wallet
    • Progressive Leave Policies
    • Unlimited Holidays
    • Monthly Wellness Stipend (towards physical or mental health services)
    • Volunteer Days Off
    • Regular (Remote) Socials
    • Paid Training/Events (relating to your role)
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