Senior Data Scientist | Remote

Crossing Hurdles; United States; Remote; CAD 189,049 - 302,479; Part time

Job summary

A data science consultancy is seeking experienced and credentialed Data Scientists for remote work. This role focuses on training and enhancing AI systems across diverse fields such as quant trading and bioinformatics. The ideal candidates should have strong credentials, typically a PhD or MS in a related field, along with industry experience and proficiency in cloud-based data tools. Compensation is hourly, ranging from $100 to $160, with a commitment of 10–40 hours per week.

Qualifications

• Strong credentials in data science, typically a PhD or MS in a related field.
• Industry work experience in quant trading, bioinformatics, astrophysics, applied computational mathematics, or similar.
• Experience with cloud-based data and ML tools.

Responsibilities

• Work on projects that focus on training and enhancing AI systems.
• Apply data science expertise in various domains like quant trading and bioinformatics.

Skills

Data science expertise

Cloud-based data tools proficiency

Quantitative analysis

Bioinformatics knowledge

Astrophysics understanding

Applied computational mathematics

Education

PhD or MS in a related field

Tools

Google Colab

BigQuery

Databricks

Snowflake

AWS/Azure analytics tools

Job description

Position: Experienced & Credentialed Data Scientists

Type: Hourly contract

Compensation: $100-$160 per hour

Location: Remote

Commitment: 10–40 hours/week

Role Responsibilities

• Work on projects that focus on training and enhancing AI systems
• Apply data science expertise in domains such as quant trading, bioinformatics, astrophysics, and applied computational mathematics

Requirements

• Strong credentials in data science, typically a PhD or MS in a related field
• Industry work experience in fields such as quant trading, bioinformatics, astrophysics, applied computational mathematics, or similar
• Experience with cloud-based data and ML tools such as Google Colab, BigQuery, Databricks, Snowflake, or AWS/Azure analytics tools