Data Scientist at Spriggy

Full-Time, None, Sydney, New South Wales sydney full-time
Posted a month ago

About Spriggy:

Spriggy helps Aussie families teach their kids about money. Our flagship app provides parents with a safe and simple app that they use to pay their kids pocket money, set chores, manage savings and monitor spending. Kids are provided with a personalised prepaid card and an app they use to learn about earning money, responsible spending, and the importance of saving. Our up and coming products include an app to help manage daily school life and an investment app to ensure the financial wellbeing of kids right into early adulthood.

Spriggy launched in late 2016 and has had over 500,000 members join, with hundreds of new parents and kids joining Spriggy every day. Spriggy is backed by high-calibre Australian investors, including Mike Cannon-Brookes' Grok Ventures and NAB Ventures, and are now looking to grow our team.

We’re a highly capable, fast-growing team, with people from backgrounds that include engineering, design, physics, genetics, medicine and mathematics… we even have a professional golfer on the team! We’re all passionate problem solvers who are eager to help Aussie families teach their kids about money.

The opportunity:

Spriggy has experienced rapid growth over the last 5 years and we’re now looking for an experienced Data Scientist. As a Data Scientist, you will utilise your experience in data engineering and analysis to support business decision making. Reporting to the Engineering Manager, you’ll work as an integral member of our product teams requiring you liaise with the Product Managers, engineers and stakeholders on a daily basis. We have lots of room to grow in Spriggy and you’ll have the opportunity to be a part of this journey.

About you:

  • You’re a team player. Your biggest sense of accomplishment comes from positive feedback from the colleagues around you. You have worked with Product teams and Product Managers before and enjoy working across multiple cross-functional teams.
  • You’re a strong communicator. You will have outstanding communication skills to a diverse audience, including non-technical and technical stakeholders.
  • You understand that the process of building great software goes beyond technical considerations. You understand the importance of working with stakeholders to get the complete picture when decision making. You’re not afraid to ask questions when things aren’t clear to you and you put all of this context together to drive your decision making process.
  • You’re autonomous. We’re a small team with one Senior Data Scientist on the team. You’re comfortable working with others but you’re also experienced in leading the way with minimal management.
  • You’re focused on outcomes not outputs. How can we measure success? What are we going to do once the feature has been shipped? You’re not precious about any one solution, because you know that exploration and iteration gets you to the right answer. You recognise that the best solutions often involve small thoughtful iterations at speed.
  • You love the startup environment or are keen to see what it’s like. If you’ve worked in a startup before you know what it’s like and love it. If you haven’t, you’re keen to try it out and see how a successful startup operates.

About the role:

  • Work collaboratively within a cross-functional team led by a Product Manager. Team members may come from disciplines such as engineering, product, design, operations or analytics and operate with a sense of shared purpose.
  • Collaborate closely with stakeholders in short, iterative sprints to achieve business objectives.
  • Collaborate with cross-functional teams to understand their business needs, formulate and complete end-to-end analysis that includes data gathering, analysis, insights and deliverables.
  • Implement data engineering solutions using tools and frameworks such as Git, AWS, Terraform, Hive & Spark.
  • Work hands on in the code, writing primarily in Python with an eye for maintainability.
  • Constructs datasets using libraries such as Pandas, NumPy and SciPy.
  • Make recommendations around architecture, efficiency and data quality.
  • Maintain clear and easily accessible documentation and processes.
  • Proactively conduct deep dives into our product and business metrics and focus areas to surface actionable insights
  • Act as a data-driven partner to our Product Managers and Product Leadership team to support measurement and insights of our feature releases.
  • Identify insights and opportunities through exploratory analysis, including assessing trends, cohorts, funnels, and user flows
  • Drive consistency within our internal eventing processes and taxonomy to ensure we have the right data foundations and tracking in place
  • Leverage our product analytics tool, Amplitude, to deliver, build and maintain high quality product analytics for the product teams.
  • Deliver effective presentations of findings and recommendations to technical and non-technical stakeholders.
  • Develop and automate reports, iteratively build and prototype dashboards to provide insights at scale, solving for analytical needs.

Key skills:

  • Experience working with data engineering tools such as Python, Git, Hive, Terraform.
  • Experience working with cloud providers such as AWS or Azure
  • Experience collaborating with technical and non technical stakeholders.
  • Experience working autonomously in a small team.
  • 5+ years experience.

What you’ll get:

  • Work at one of Australia’s fastest growing Fintechs alongside some of the best and brightest.
  • An excellent culture, we encourage collaboration, growth and learning amongst the team.
  • A competitive salary.
  • An ability to directly influence the direction of the Spriggy product and business.
  • An autonomous and flexible role where you will be trusted with key tasks.
  • An opportunity to have real impact and be part of a company with purpose.
  • A flexible workplace environment.