DATA SCIENTIST

What We're Looking For We are seeking a skilled Data Scientist with expertise in Python and experience handling geospatial data and demographic/economic data.
This role is crucial in driving our data-driven solutions and analytics that inform credit decisions and business strategy.
You'll collaborate across teams to deliver insights from diverse data sources and help shape the direction of our credit solutions.
Responsibilities Analyze and interpret large datasets, including geospatial data and demographic/economic data, to generate actionable insights for our credit solutions.
Build and optimize machine learning models, leveraging these data sources to improve credit assessments.
Collaborate with engineering, product, and business teams to implement data-driven strategies.
Design and maintain data pipelines that ingest, clean, and transform various data types.
Perform exploratory data analysis and create visualizations to communicate insights to technical and non-technical stakeholders.
Contribute to the development of our data architecture and strategy to scale data science capabilities At AltScore, we believe in providing our team members with a comprehensive benefits package that supports their overall health and wellbeing.
We offer the following compensation package to eligible employees.
Base Salary.
$ USD per month, depending on skills according to our engineering scale L3 - L8.
Performance Bonus.
Based on achievement of agreed KPIs.
Unlimited PTO (with an expectation of taking at least 3-4 weeks per year off) We understand that maintaining a healthy work-life balance is crucial for long-term productivity and wellbeing.
Employee stock ownership plan (ESOP) - Every single employee gets an ESOP.
At AltScore, we believe that every member of the company should feel like a partner from day 1.
Remote.
At AltScore, we are a fully remote company, and we encourage employees to work from wherever they are most comfortable and productive.
Employees must work in the Americas timezone.
Bachelor's or Master's degree in Data Science, Computer Science, Engineering, Economics, or a related field.
Proficiency in Python (2+ years of experience or the equivalent hours of deliberate practice), with experience in data manipulation and analysis libraries (Pandas, NumPy, etc.).
Experience with visualization libraries and data representation techniques.
Experience working with geospatial data and demographic/economic datasets.
Familiarity with statistical analysis and machine learning techniques.
Experience working with APIs for data integration.
Strong communication skills and the ability to translate complex data insights into business terms.
Ability to work autonomously and collaboratively in a fast-paced environment.