Summary

The Role

This role is part of our Block Risk Labs team which sits within our Risk organization. This team's mission is aimed at developing advanced deep learning and reinforcement learning based signals and learned representations for ML models. Our team has the mandate to explore, develop and implement alternatives to traditional feature based ML with SOTA models for solving risk problems.

You Will

1. Report to the lead of the Risk Labs Modeling team
2. Lead the conception, design, and implementation of large-scale experiments to validate novel ideas rapidly and comprehensively.
3. Apply the latest theoretical advancements to enhance existing products, processes, and technologies, ensuring they remain at the forefront of the industry.
4. Engage in the creation of experiments, prototyping, and architectural design, contributing to a diverse range of computer science domains such as machine learning, data mining, natural language processing, and performance analysis.
5. Contribute to the growth of new initiatives by sharing emerging trends and best practices, fostering a collaborative and innovative environment.
6. Take the lead in defining data structures, frameworks, designs, and evaluation metrics for applied research solution development, exhibiting autonomy in decision-making.
7. Collaborate with internal and external partners, identifying potential applied research areas and participating in the development of long-term development strategies.
8. Conduct experiments aligned with applied research inquiries, employing simulations and prototypes to assess the outcomes of investigations.
9. Refine research methodologies, solidifying hypotheses, and contributing to the evolution of applied research practices under minimal supervision.

You Have

1. Minimum of 5 years of hands-on experience in full-time professional, data-heavy, and machine learning focused role.
2. An advanced degree (PhD preferred) in a quantitative field (computer science, physics, math, etc) with significant experience using and developing machine learning and AI methodologies.
3. Proven experience in conducting applied research projects with tangible outcomes.
4. A demonstrated history of generating intellectual property within the field. These contributions could take the form of open source software, patents, or refereed publications in venues such as conferences, journals, books, etc.
5. Proficiency in machine learning techniques, data mining, experimental design
6. Strong programming skills in languages such as Python, TensorFlow, or PyTorch.
7. Creative mindset to tackle complex challenges.
8. Experience collaborating with cross-functional teams and contributing to the applied research community.

Technologies We Use and Teach

1. Python
2. NumPy, Pandas, sklearn, xgboost,
3. TensorFlow, Pytorch, keras, etc
4. MySQL, Snowflake,
5. GCP/AWS and
6. Spark

Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.

To find a location’s zone designation, please refer to this resource. If a location of interest is not listed, please speak with a recruiter for additional information. 

Zone A:

$228,700—$343,100 USD

Zone B:

$217,300—$325,900 USD

Zone C:

$205,900—$308,900 USD

Zone D:

$194,500—$291,700 USD

Skills

• AWS
• Communications Skills
• Database Management
• Development
• Machine Learning
• Python
• SQL
• Team Collaboration