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7 дней назад

Senior Data Scientist Embedded Insights

191 000 - 263 000$
Формат работы
hybrid
Тип работы
fulltime
Грейд
senior
Страна
US
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Описание вакансии

TL;DR
Senior Data Scientist Embedded Insights (Machine Learning/Data Science): Establishing analytics and metrics for network, product, customer, and machine learning products with an accent on model evaluation, experimentation, dashboards, and reliable data workflows. Focus on analyzing network behavior and risks, designing experiments with success metrics and guardrails, and connecting technical findings to business outcomes.

Senior Data Scientist Embedded Insights

Company

Plaid Inc.

Conditions

1 day agoSalary: 191K - 263K

Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will establish analytics and metrics for internal and external products. You will analyze network, product, and customer data; create dashboards and monitoring; evaluate machine learning models; design experiments; identify improvements; and build reliable data models and analytics workflows with cross-functional partners.

Requirements

  • 6+ years of industry experience in data science or a related analytics role.
  • Familiarity with SQL and data visualization tools.
  • Understanding of machine learning techniques including classification, clustering, and optimization.
  • Experience evaluating model performance and connecting technical results to business outcomes.
  • Experience tailoring analytical solutions to business problems with cross-functional partners.
  • Python experience for exploratory data analysis.
  • Written and verbal communication skills for technical and non-technical audiences.

Responsibilities

  • Analyze network entities to identify behavior, opportunities, anomalies, and risks.
  • Create metrics, dashboards, and monitoring systems for network health and model performance.
  • Evaluate machine learning model value and performance.
  • Identify model improvements and communicate actionable findings.
  • Design experiments, define success metrics and guardrails, analyze results, and communicate recommendations.
  • Analyze product and customer data for improvement and expansion opportunities.
  • Partner with cross-functional teams to build reliable data models and analytics workflows.

Benefits

  • Equity
  • Medical insurance
  • Dental insurance
  • Vision insurance
  • 401(k)

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