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Full-Time

Senior Data Scientist

Posted on 4/13/2024

Metropolis

Metropolis

201-500 employees

Computer vision-based parking and payment solutions

Data & Analytics
Fintech
AI & Machine Learning
Financial Services
Real Estate
Consumer Goods

Compensation Overview

$150k - $190kAnnually

+ Stock Options + Bonus Plans

Senior

Los Angeles, CA, USA

Category
Data Science
Data Engineering Management
Data Analysis
Data & Analytics
Required Skills
Python
Data Science
R
Data Structures & Algorithms
Apache Spark
SQL
Pandas
Hadoop
Requirements
  • Bachelor's degree or higher in Statistics, Mathematics, Computer Science, Engineering, or a related field. Masters or Ph.D. Degree preferred.
  • 5+ years of experience working as a data scientist, with a proven track record of delivering impactful data science solutions.
  • Proficiency in programming languages such as Python or R, along with experience using libraries and frameworks for data manipulation, analysis, and modeling (e.g., pandas, ggplot, scikit-learn).
  • Proficiency in SQL and understanding of OLTP/OLAP databases.
  • Strong understanding of statistical analysis, hypothesis testing, and experimental design principles, with experience conducting A/B tests and analyzing experimental data.
  • Experience working with large-scale datasets and distributed computing frameworks (e.g., Hadoop, Spark) is a plus.
  • Excellent communication skills with the ability to translate complex technical concepts into actionable insights for non-technical stakeholders.
  • Proven ability to work effectively in a collaborative, cross-functional environment, with a demonstrated track record of building successful partnerships with product and engineering teams.
  • Strong problem-solving skills and a passion for leveraging data to drive business impact and improve user experiences.
Responsibilities
  • Analyze large-scale datasets to identify trends, patterns, and insights that inform product and engineering strategy and decision-making.
  • Design and implement key metrics and statistical experiments to evaluate the impact of new products and feature enhancements.
  • Prototype predictive models and algorithms to identify signals and accelerate data-driven decisions.
  • Communicate findings and recommendations to stakeholders through clear and compelling data visualizations, reports, and presentations.
  • Collaborate with cross-functional product and engineering teams to define, influence, and support initiatives aligned with business goals.
  • Stay updated with the latest advancements in data science, machine learning, and experimentation techniques, and explore innovative ways to apply them to product and engineering development.

Metropolis utilizes computer vision and machine learning to revolutionize parking, eliminating the need for cash, credit cards, or tickets. The company is also exploring technology for enabling "checkout-free" experiences in physical spaces, enhancing the overall parking and payment experience.

Company Stage

Series C

Total Funding

$1.9B

Headquarters

Santa Monica, California

Founded

2017

Growth & Insights
Headcount

6 month growth

17%

1 year growth

23%

2 year growth

31%
INACTIVE