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Director of Data Science

Level: Leadership
Capacity: Full time
Type: Employee
Location: Dexibit’s Auckland office
Reports to: VP of Engineering

Who we are and what we do

Do you love dinosaurs and data? At Dexibit we’re a kiwi SaaS company providing big data analytics to visitor attractions. From museums to zoos to theme parks, we work with big names such as the Smithsonian, Royal Palaces and NASA alongside your favourite places here in New Zealand like MOTAT and Weta. We’re a diverse, empowered team who have collected a fair few awards in our time from HiTech, NZIBA, TIN and more! 

Dexibit predicts and analyses visitor behaviour to help bring more visitors through the door, engaging and coming back. Our product includes forecasts, insights and dashboards powered by machine learning, natural language processing and more. We serve predominantly larger venues through an enterprise sales business model.

There’s never been a more important time to help the world’s culture and entertainment sectors as they reopen and recover after COVID-19. Being early in our journey, internationally focused and with an exciting modernisation program underway too, there’s lots of opportunities for career growth.

Data Science at Dexibit

At Dexibit, we’re a product company and data is the product at the heart of everything we do. Data science sits right at the center – powering predictions and insights for our users to take our offering beyond data consolidation and visualisation. Our data scientists and machine learning engineers work as a team with a dual purpose of deep research and supporting our product teams across discovery and delivery to bring innovative ideas to market at scale.

This is a hands-on lead role with its own contribution plus people management responsibilities in charge of a small but mighty data science practice. Alongside three cross-functional product development teams, this forms part of our wider technology team. It’s a great opportunity for an experienced data science practitioner with leadership exposure to take the next step in management progression, with the added challenge of doing so with data science as a product – going beyond data science as an internal function or consulting service and instead serving an international market at scale.

Our data science team manages their work through Jira alongside the Atlassian suite and code through Git and Bitbucket. We use SQL/Python to extract and manipulate data and Python for machine learning or statistical analysis. We have our own productised machine learning pipeline and framework hosted on AWS, utilising a range of AWS services but we are in the process of investigating and adopting a third party stable and enterprise-ready machine learning platform (Databricks).

What you’ll get up to

Strategically, you’ll coach our data scientists in forming, pitching and pursuing strategic research to keep pushing the boundaries on how we innovate to solve hard problems for our customers.

Operationally, you’ll ensure our various models are performing in the wild with a continuous improvement focus on accuracy our users can trust. This may involve responding to real world challenges and updating our models accordingly.

You’ll lead our data science efforts across discovery and delivery, ensuring the right processes are implemented and being practiced. This could include sprint planning, stand ups, code reviews, deployments, demos, and retrospectives.

As a thought leader in your field, you’ll be an advocate for data science as part of a larger product context, contributing to our business and technology strategy. You’ll work with different functions including marketing, sales and success teams to provide data science knowledge and support.

Our team is huge on personal development, so you’ll enjoy regular team learning and reading group sessions to keep your mind sharp. We provide opportunities to take you to new technical places or leadership challenges, and the chance to share your own knowledge with the team.

Key responsibilities

  1. Leadership of and contribution to data science research, strategy and projects.
  2. Active participation in the wider leadership team for company vision, strategy and culture.
  3. Management of data science project life cycle, including discovery and delivery.
  4. Accountability for the data science technical operations, including the monitoring, reporting and continuous improvement of accuracy, applicability and other metrics of success.
  5. Guiding experimental data science initiatives towards valuable product outcomes.
  6. Hands on engineering contribution to data science pipelines, in different domains including forecasting and natural language processing.
  7. People care for the data science team, including recruitment, onboarding, 1-2-1s, performance reviews, and professional development.
  8. Being a thought leader to promote data science within Dexibit and in the wider community. 

What you’ll bring

  • A Master’s degree or higher in data science, analytics, mathematics, statistics, computer science or a related discipline and 5+ years commercial experience.
  • Confidence navigating hard problems and sound judgment to assess risk with a mix of strategic thinking and attention to details.
  • Exposure to leadership in a technical coach, project lead or people management role.
  • Expertise in Python and SQL, ideally with experience in cloud technologies.
  • Practical experience with machine learning and/or natural language in a business setting, bonus points for experience setting up and using Databricks.
  • An understanding of SaaS mechanics, a solid understanding of modern product discovery and delivery processes and agile practices.
  • Key organisation and communication skills, including the ability to simplify complex concepts to engage in marketing and customer facing presentations.

Bonus points for experience in international markets or in a software company, particularly where data is the focus.

A day at Dexibit

Our teams operate in a flexible way, with a mix of in office or remote work options. A typical day in our data science team starts with a routine standup meeting. Our team are often early starters to make the most of our time zone window with our team overseas or to connect directly with customers globally. 

As part of planning, you might talk about an upcoming sprint or jump on a call with one of our customers to learn how the industry works and how our product enables them. You might be designing a new model or automating it within our product framework, or investigating opportunities for improvement with an existing model and testing new features. 

Each week, you’ll also have a regular 1:1 chat with your manager to make sure you’re always growing and learning and likewise, host the same for your direct reports. You might also meet with other leaders across the company to find ways our teams can collaborate more or to discuss strategic directions.

In addition to the sprint cycle, each week our team gathers for fun social events such as kitchen teas, brown bags and happy hours, with lots of opportunities to mix with our second office in Washington DC. Once a quarter the wider company team assembles for a comprehensive business review to provide strategic context and the chance to connect with other aspects of the company – plus our legendary team building outings which take us out to enjoy unique visitor experiences first hand. 

Céline Rufener

VP of Engineering

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