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Data Scientist, Sales

Wealthsimple Remote (Canada)Est. Est. CAD 120,000–170,000 / yearSenior

Estimated range based on role, country and industry — not published by the company.

Key requirements

  • Python
  • Sql
  • Airflow
  • Dbt
  • Data Science
  • Stakeholder Management
Build something people love Wealthsimple is Canada’s leading financial innovator. The company offers a full suite of simple, sophisticated financial products across managed investing, do-it-yourself trading, cryptocurrency, tax filing, spending and saving. Wealthsimple currently serves more than 4 million Canadians and holds over $155 billion in assets under administration. The company was founded in 2014 by a team of financial experts and technology entrepreneurs, and is headquartered in Toronto, Canada. We're proud of what we've built — and we're just getting started. Read our Culture Manual and learn more about how we work . The Sales Data team is responsible for supporting the entire Commercial team through data modeling, pipelining, dashboarding, experimentation, analyses, and machine learning models. Our stakeholder teams are diverse, including Financial Planners & Advisors, Business Development Representatives, our AI Voice Agent team, Revenue Operations and Commercial Systems.   We are looking for a Senior Data Scientist who has strong foundations in data modeling and machine learning to lead high priority initiatives, take ownership as a decision science expert, and help shape the direction of our Commercial team and our AI Voice Agent program.   Some of your projects may include: modeling sales data, creating and improving reporting for business stakeholders, exploratory data analysis to improve our sales processes, and developing and maintaining ML models. Our models are used to solve real business problems and directly impact Wealthsimple’s north star metric. Therefore, experience with supporting sales is a bonus.   In this role, you will have the opportunity to:   Build and maintain new data models that are accurate and reliable Work closely with a wide range of stakeholders from Data Science, Commercial Leadership, Sales Operations, Product, Design, and Engineering Define, prototype, implement and improve ML models Design experiments to test hypotheses (e.g. which customers should we focus on in our outbound calls) Build/maintain reports, dashboards, and metrics to support our north star metrics Teach and learn from their teammates. We value making others successful   What you bring:   5+ years of experience in a data science/decision science (or equivalent), including time as the primary DS for a domain Excellent SQL & Python skills - hands-on experience with data pipeline tools such as dbt and Airflow are an advantage Strong stakeholder management skills - an excellent communicator who is able to present results and analyses to senior leadership Good understanding of business practices, sales, and client behavior Experience with applied statistics or experimentation (i.e. A/B testing) in an industry setting Understanding of fundamental machine-learning algorithms and experience putting them into production in a real-world context Experience in managing/mentoring team members in a formal or informal capacity Why Wealthsimple? 🌸 Top-tier health benefits and life insurance 📈 Long-term group savings with employer match, through Wealthsimple for Business 🌴 20 vacation days, 4 wellness days, and unlimited sick and mental health days per year* ✈️ 90 days away: work outside Canada for up to 90 days per year* 👥 Employee resource groups, including Rainbow (2SLGBTQ), Women of WS, and Black at WS 🌎 We are a hybrid team with over 1,500 employees across North America. The people are one of the best parts of working here: you'll collaborate with incredibly talented, curious, and driven teammates who are deeply committed to doing great work. *Unlimited paid sick days, Wellness Days and the 90 day away program do not apply to certain roles. ICYMI Technology & Innovation at Wealthsimple: We move quickly and build thoughtfully. That means we're always looking for better ways to work — whether that's new tools, AI, or rethinking how we approach a problem. We don't

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