Remote Senior Data Scientist - Machine Learning

Placements24; United States; Remote; USD 120,000 - 160,000; Full time

Benefits offered by this job

Performance bonuses

Health insurance

Fully remote work

Professional development budget

Job summary

Placements24 is seeking a Senior Data Scientist with expertise in machine learning to design, develop, and deploy advanced models in a remote-first R&D team. This role supports operations with a global reach, enabling data-driven decisions and innovative research without geographical constraints.

The candidate will work with large datasets, collaborate with cross-functional teams, and mentor juniors while staying current with ML advancements.

Qualifications

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or related quantitative field.
• 6+ years of professional experience as a Data Scientist with a strong ML focus.
• Proficiency in Python or R and ML libraries (TensorFlow, PyTorch, Scikit-learn).
• Strong statistical modeling, experimental design, and data mining understanding.
• Experience with cloud platforms (AWS/Azure/GCP) and distributed computing.
• Excellent communication and ability to work independently in a remote environment.

Responsibilities

• Develop, train, and evaluate ML models for prediction, classification, and clustering.
• Implement and optimize ML algorithms for large-scale datasets.
• Collaborate with engineers and product managers to deploy models.
• Perform exploratory data analysis and feature engineering.
• Stay updated on ML, DL, and AI research trends.
• Mentor junior data scientists and help grow the team.

Skills

Python/R

TensorFlow

PyTorch

Scikit-learn

Cloud platforms

Distributed computing

Remote work

Education

Master's or Ph.D. in CS/Statistics/Math

Tools

AWS

Azure

GCP

Job description

Our client is seeking a highly motivated and experienced Senior Data Scientist specializing in Machine Learning to join their expanding, remote-first R&D team, supporting operations in the Paarl region. This critical role involves designing, developing, and deploying advanced machine learning models to solve complex business problems and drive innovation. You will work with large datasets, collaborate with cross-functional teams, and contribute to the strategic direction of data-driven initiatives. This is an exceptional opportunity for a seasoned data scientist to leverage cutting-edge ML techniques in a fully remote setting, influencing product development and research outcomes without geographical constraints.

Key Responsibilities

• Develop, train, and evaluate sophisticated machine learning models for prediction, classification, and clustering tasks.
• Implement and optimize ML algorithms for large-scale datasets, ensuring scalability and efficiency.
• Collaborate closely with engineers and product managers to integrate ML models into production systems and research projects.
• Perform exploratory data analysis and feature engineering to uncover insights and improve model performance.
• Stay current with the latest advancements in machine learning, deep learning, and AI research.
• Mentor junior data scientists and contribute to the team's technical growth and best practices.

Requirements

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Minimum of 6 years of professional experience as a Data Scientist with a strong focus on Machine Learning.
• Proficiency in programming languages such as Python or R, and extensive experience with ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong understanding of statistical modeling, experimental design, and data mining techniques.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and distributed computing frameworks.
• Excellent communication skills and proven ability to work independently and effectively in a remote environment.

Benefits

• Highly competitive annual salary with performance-based bonuses.
• Comprehensive health, dental, and vision insurance.
• Fully remote work arrangement with a flexible schedule.
• Generous budget for professional development, training, and conference attendance.
• A collaborative and innovative team culture, fostering continuous learning and cutting-edge research.