Data Scientist & Business Intelligence Lead
Airtasker is a fast-growing online and mobile marketplace for local services and temporary labour. We are revolutionising the way people and businesses get more done by connecting real time labour requirements with one of the world's most under-utilised assets - people power.
Airtasker has big ambitions and recently raised $33M worth of funding as we go international, with UK being the first country to plant our flag! We are building a talented team with opportunities to make a real impact in a hyper-growth and solutions-oriented start-up workplace.
We are looking for a Data Scientist & Business Intelligence leader who will spearhead the creation and nurturing of our data science environment. You will be responsible for implementing best practice, as well as building and leading a team of data scientists and business analysts.
Together, you and the team will be collaborating closely with our product managers, engineering team and designers to deliver positive experiences to our Airtasker community, as well as increasing commercial outcomes.
Being a key business partner & leader:Being the Chief Evangelist for setting and promoting the culture and mission for data science and business intelligence at Airtasker Leading the team, including building roadmaps/setting priorities, and being responsible for their learning and developmentProviding high-level business insights to all functional teams by constantly looking at available data and its relationshipsConsistently identifying and monitoring key business risks and realising the data needs of the business, including projecting seasonality trends and task volumesWorking with key stakeholders on ad hoc projects and provide a data centric perspectiveReducing the cost of the Operations team around labour intensive tasks like moderation
Ensuring best practice:Ensuring Airtasker is aware of best practice around insights in data specific to marketplaces and set the stage to becoming pioneers in data science, business intelligence and analyticsPlaying a strategic role in continuously improving Airtasker's data analysis model, creating industry-leading performance through the leveraging of new and creative data-sources, and employing the latest in machine learningMaintaining a deep understanding of Airtasker's marketplace dynamics and takes initiative in conducting exploratory data analyses and experimental designs to drive success of business goals and targets
The creation & setup of systems:Setting up systems for organising and presenting data, and an infrastructure that can scale along with the businessSetting up, with the engineering team, a dynamic yet stable data science infrastructure, including a data warehouse and appropriate data visualisation toolsDesigning and launching innovative and complex analytic models, utilising a blend of contemporary and traditional data mining techniques, which applies to both structured and unstructured data setsEnsuring that the integrity of data quality at Airtasker is maintained and constantly improved
Essential attributes that we are looking for:5+ years of industry experience preferred, along with some experience in managing teamsA degree in a quantitative field (e.g. Statistics, Actuarial, Data Science, Mathematics, Computer Science)Comfortable dealing with large, unstructured and real time dataAble to work in an Agile manner, iterating through MVP to highly-evolved conceptsProven experience in successfully implementing data infrastructureStrong understanding of statistics and machine learningAbility to work collaboratively with a wide range of key stakeholdersA champion of best practice implementation, with a focus in executing impactful changeExcellent English communication skills
Desired:Working knowledge of LookerPractical PostgreSQL and Redshift experienceExperience with Git or other source control software, having contributed to the open source communityElasticsearch with keyword scoring and geospatial searching capabilityInterest in the start-up and technology community
Posted by Airtasker