Senior Data Scientist

Twilio

15h•$141,520 - $208,000•Remote

About The Position

This position is needed to uncover analytical insights that quantify product performance and shape product strategy. Our Data Science and Analytics team seeks to empower R&D to make data-backed decisions that accelerate innovation and improve product performance. We work closely with Product Managers to define product metrics and build self-serve reporting; measure the impact of product releases; and do analyses to shape strategic decisions.

Requirements

2+ years of professional experience in an analytics or data science role
Advanced expertise using SQL to derive insights and in using dashboarding tools like Looker or Tableau to create compelling self-serve reports for product or business stakeholders
Intermediate expertise in Python (e.g. pandas, numpy, scikit-learn) for data manipulation, analysis, and statistical modeling (e.g., clustering, forecasting, or decision trees)
Familiarity with causal inference techniques such as A/B testing, propensity matching, or synthetic control
Demonstrated ability to map business problem statements to an appropriate data science technique
Answer-first, succinct communication; ability to communicate across technical and non-technical audiences

Nice To Haves

4+ years of professional experience in a product-focused analytics or data science role, with 2+ years of experience in a B2B SaaS context
Bachelor’s and Master’s in a quantitative
Familiarity with machine learning techniques
Experience with data warehousing and/or ETL processes, including distributed computing technologies such as Hive, Presto, or Spark

Responsibilities

Drive the definition and development of data science solutions to business problem statements from beginning to end: build relationships with partner teams, collect and analyze data, and develop recommendations to inform strategic decisions
Generate insights and recommendations through exploratory analysis, A/B testing, and statistical modeling
Work with product managers to design and analyze experiments to measure the impact of new features and develop a data-driven narrative on how their product is performing for use in monthly reviews
Collaborate with data producers and consumers during the product development lifecycle to ensure consistent data quality and availability for reporting post launch.