current openings
Current opening in Toronto
Data Scientist
Toronto

The Opportunity

MightyHive is the leading data and digital media consultancy that helps marketers take control. MightyHive delivers sustained results from the ground up through advisory for business transformation, privacy-first data strategy, and digital media services.

The company is headquartered in San Francisco, with a team of consultants, platform experts, data scientists, and marketing engineers in 19 countries and 24 cities around the world. In 2018, MightyHive merged with S4Capital plc (SFOR.L), a tech-led new age/new era digital advertising and marketing services company established by Sir Martin Sorrell.

We are looking for a Data Scientist to join our growing Canadian team. This is a new role focused on the use of data and models to gain granular insight into digital media performance, support fact-based decisions, and communicate opportunities for improvement for MightyHive’s clients as well as our internal initiatives.

 

The Role

The Data Scientist will help develop solutions using statistical, data mining methods and data engineering solutions, working closely with our Analytics, Account Management, and Solutions Engineering teams. The candidate can expect to participate in all phases of internal and client projects, including project definition, data discovery, data engineering, model development and/or data mining, evaluating options, and making recommendations.

 

Responsibilities include:

  • Mine data to support analytical projects and prepare data to support the development of information models to prove or disprove project hypotheses
  • Use statistical analysis and machine learning libraries (R Stats, Python StatsModels, scikit-learn, etc.) to create models that quantify the influence of online activities on offline conversions
  • Design and manage experiments to ensure proper execution, data cleanliness, and statistical significance of results
  • Utilize data visualization techniques to explain data and models to clients and internal teams (Tableau, Looker, Data Studio, etc.)
  • Nurture client understanding of the importance of building & testing strategies across media buys; act as a consultative resource to help clients understand the quality of their internal testing processes
  • Integration of technology platforms and amalgamation of disparate client data sources
  • Deploy cloud resources to perform analysis on large data sets

 

What you bring to it:

  • Strong analytical problem-solving skills and ability to work with incomplete or imperfect data
  • Relevant mathematics background including Statistics, Calculus, and Linear Algebra
  • Bachelor’s/Master’s degree in Computer Science, Engineering, Management of Information Systems, Mathematics, Statistics/Economics or relevant field
  • 1+ years of experience in digital analytics and digital advertising
  • 1+ years of experience querying large databases (SQL) (experience with BigQuery a plus)
  • 2+ years of experience analyzing data with Python and/or R
  • 1+ years of experience with site-wide analytics tool (Google Analytics/Adobe Analytics)
  • Able to read/write basic HTML/HTML5/CSS/JavaScript
  • Hands-on experience with machine learning algorithms for classification, regression, and prediction (example, scikit-learn, StatsModels, etc.)
  • Experience reading the API documentation and understanding the technical requirements for implementation with other platforms
  • Passionate about working in an extremely fast-paced, demanding, and fluid startup environment
  • Ability to explain the analytical methods and results to non-technical stakeholders to drive data-driven decision making

 

What we offer:

  • Competitive salary + year-end bonus tied to Company performance
  • Competitive group health plan
  • RRSP Pension plan 
  • 4 weeks vacation per year
  • Ability to work remotely
  • Flexible working hours
  • Training program and career pathing
  • Potential for global travel
  • Fast paced startup environment on the bleeding edge of technology changes
  • Casual/flexible environment 
  • Working remotely during the COVID-19 pandemic