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Senior Machine Learning Engineer (Embedded Insights)

Plaid

Skills

Required

  • machine learning
  • Data Science
  • SQL
  • Python
  • data visualization

Join Plaid, a company on a mission to unlock financial freedom for everyone. As a Senior Machine Learning Engineer on the Embedded Insights team, you will build machine learning-powered products and features, initially supporting the Plaid App. You will work closely with product managers, data scientists, engineers, customers, and other machine learning engineers to translate ambiguous opportunities into effective ML systems that create measurable customer value.

USD 228,960 - 315,360

About Plaid

We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!

Responsibilities

  • Construire des fonctionnalités basées sur l'apprentissage automatique pour un produit destiné aux consommateurs.
  • Collaborer avec les chefs de produit pour traduire les exigences commerciales ambiguës en problèmes d'apprentissage automatique.
  • Analyser les ensembles de données uniques de Plaid pour identifier les opportunités d'apprentissage automatique à fort impact.

Requirements

  • 6+ years of experience in machine learning, including deploying models into real-world, customer-facing systems
  • High agency and creativity, with experience identifying, defining, and proposing high-impact machine learning opportunities
  • Experience taking machine learning systems from experimentation or proof of concept through production and ongoing improvement
  • Ability to analyze large and complex financial datasets and derive actionable insights
  • Advanced degree or equivalent work experience in Statistics, Economics, Mathematics, Data Science, or a related field
  • Proficiency in SQL and Python, as well as data visualization and analysis tools
  • Ability to clearly communicate complex technical systems, decisions, tradeoffs, and outcomes to cross-functional partners