Remote Data Scientist - Resource Modeling

Placements24; Willows (CA); Remote; USD 120,000 - 190,000; Full time

Benefits offered by this job

Remote work

Home office stipend

Flexible hours

Tech upgrades

Job summary

Placements24 is seeking a highly analytical Remote Data Scientist to join a globally distributed team focused on mineral resource estimation. You will leverage big data, ML, and statistics to improve accuracy and efficiency of resource models, collaborating with geologists, engineers, and data analysts worldwide.

The role emphasizes remote collaboration, advanced modeling, and experimentation, with opportunities to contribute to data-driven exploration strategies and receive flexible hours and

Qualifications

• Master’s or PhD in a quantitative field.
• 6+ years of data science experience with statistical modeling.
• Proficiency in Python or R and ML libraries.
• SQL proficiency with large datasets.
• Experience with cloud platforms and big data tech.
• Strong communication for remote work.

Responsibilities

• Develop, implement, and validate predictive models for mineral resource estimation and grade prediction.
• Utilize ML algorithms to identify patterns in large geological datasets.
• Clean, transform, and prepare diverse datasets for analysis, ensuring data integrity.
• Collaborate with cross-functional teams remotely to understand data needs and deliver insights.
• Design and conduct A/B tests and experiments to evaluate model performance.
• Communicate complex findings and model methodologies clearly to technical and non-technical audiences.

Skills

Statistical modeling

Remote collaboration

Data storytelling

Education

Master’s or PhD in Data Science/Statistics/CS

Tools

Python

SQL

scikit-learn

TensorFlow

PyTorch

AWS/Azure/GCP

Job description

About the Role

Our client is seeking a highly analytical and innovative Remote Data Scientist to join their globally distributed team, focusing on advanced resource modeling for mining operations. This fully remote position allows you to leverage big data, machine learning, and statistical modeling techniques to enhance the accuracy and efficiency of our mineral resource estimations. You will collaborate with geologists, engineers, and data analysts worldwide, contributing to data-driven decision-making that shapes our exploration and extraction strategies. This is a unique opportunity to work from anywhere, contributing to significant advancements in the mining industry using cutting-edge data science methodologies.

Key Responsibilities

• Develop, implement, and validate predictive models for mineral resource estimation and grade prediction.
• Utilize machine learning algorithms to identify patterns and correlations in large geological datasets.
• Clean, transform, and prepare diverse datasets for analysis, ensuring data integrity.
• Collaborate with cross-functional teams remotely to understand data needs and deliver actionable insights.
• Design and conduct A/B tests and other experiments to evaluate model performance and impact.
• Communicate complex findings and model methodologies clearly to both technical and non-technical audiences.

Requirements

• Master’s or PhD in Data Science, Statistics, Computer Science, or a related quantitative field.
• Minimum of 6 years of professional experience as a Data Scientist, with a significant portion focused on statistical modeling and machine learning .
• Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Strong experience with SQL and working with large, complex datasets.
• Familiarity with cloud computing platforms (AWS, Azure, GCP) and big data technologies.
• Excellent communication and collaboration skills, essential for a remote work environment .

Benefits

• Highly competitive salary and potential for remote performance bonuses.
• Comprehensive health, dental, and vision insurance plans.
• Generous home office setup allowance and remote work stipends.
• Flexible working hours and the ability to work from any location.
• Access to cutting-edge technology and professional development resources.