Senior Data Scientist (Remote

About Jobgether

Jobgether is a platform that connects job seekers with remote job opportunities.

Job Summary

We are currently looking for a Senior Data Scientist in the United States. This role offers the opportunity to drive advanced analytics and AI-driven solutions in a high-impact environment.

Key Responsibilities

• Lead development projects, engaging with stakeholders to collect requirements and define machine learning solutions.
• Design, implement, and maintain machine learning pipelines including feature engineering, modeling, deployment, and overfitting diagnostics.
• Research and develop analytical and optimization methods to enhance platform capabilities.
• Identify opportunities to leverage advanced analytics to solve complex, non-routine business problems.
• Provide technical guidance, mentoring, and training to team members.
• Collaborate with product managers, developers, and data scientists to deliver impactful AI solutions.

Requirements

• 3+ years of hands-on experience using Python in data science or machine learning projects.
• Strong applied experience with machine learning on large datasets.
• Expertise in SQL for processing and analyzing structured and unstructured data.
• Proficiency in statistics, regression modeling, decision trees, random forests, SVM, clustering, and other machine learning techniques.
• Ability to translate business questions into data-driven solutions.
• Experience with Linux distributions and collaborative software development environments.
• Strong communication and data presentation skills, with a track record of mentoring or providing technical leadership.
• Bachelor’s degree in Computer Science, Data Science, or a related field, with emphasis on Machine Learning.

Benefits

• Competitive salary and performance-based incentives.
• Flexible work arrangements and supportive remote options.
• Opportunity to work on cutting-edge AI solutions in financial and operational analytics.
• Professional growth through mentoring, collaboration, and exposure to large-scale data projects.
• Inclusive and collaborative work culture valuing diversity and innovation.
• Access to learning resources and opportunities to expand technical expertise.