Build machine learning and deep learning models based on financial and other modalities like images and text
Collaborate closely with cross-functional teams to integrate machine learning models seamlessly into production systems
Conduct extensive analysis to better understand our continually evolving datasets and validate model performance
Design and develop robust, scalable pipelines and services using software engineering best practices
Implement end-to-end solutions, including architecture design, business logic, and deployment
Drive the adoption of rigorous testing practices, ensuring high-quality, reliable ML model releases
Stay updated with advancements in machine learning and related technologies to continuously improve our solutions

Requirements

Ph.D in Computer Science, Statistics, Mathematics or a related field
2+ years of relevant industry or postdoc experience
Solid understanding of computer science fundamentals, including data structures and algorithms and object oriented programming
Deep understanding of machine learning models and algorithms
Deep understanding of probability and statistics
Strong data analysis skills and experience working with messy real world data
Proficiency in python and familiarity with commonly used machine learning libraries such as numpy, pandas, torch, and scikit-learn
Excellent communication skills

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningdeep learningdata analysisdata structuresalgorithmsobject oriented programmingprobabilitystatisticsarchitecture designsoftware engineering best practices

Soft Skills

collaborationcommunicationproblem solvingadaptabilityattention to detailcritical thinkingtesting practicesreliabilityteamworkcontinuous improvement

Certifications

Ph.D in Computer SciencePh.D in StatisticsPh.D in Mathematics