Data Scientist

Stellans LLC; Sheridan (WY); Hybrid; USD 100,000 - 150,000; Full time

Benefits offered by this job

Competitive salary

Bonuses

Comprehensive insurance

Retirement with matching

Flexible schedule

Remote work options

Professional development

Tuition reimbursement

Collaborative culture

Job summary

Stellans LLC is seeking a skilled Data Scientist to develop and deploy advanced machine learning models, analyze large datasets, and uncover insights that drive business outcomes. You’ll work with cross-functional teams to identify opportunities, prototype solutions, and deliver scalable models.

You will design experiments, evaluate model performance, and optimize algorithms while implementing robust data preprocessing and feature engineering pipelines.

Qualifications

• Degree in Computer Science, Statistics, Mathematics, Engineering, or related field.
• Experience in data science, machine learning, and predictive modeling.
• Proficiency in Python and data science libraries (e.g., scikit-learn, pandas).
• Experience with ML frameworks like XGBoost, PyTorch, TensorFlow.
• Strong understanding of statistical concepts and data preprocessing.

Responsibilities

• Develop and deploy machine learning models using scikit-learn, XGBoost, PyTorch, and TensorFlow.
• Analyze datasets to identify trends and patterns that drive business value.
• Collaborate with product managers, engineers, and stakeholders to define goals.
• Design experiments, evaluate model performance, and optimize algorithms.
• Implement and optimize data preprocessing, feature engineering, and training pipelines.
• Evaluate external data sources to enhance datasets and improve model accuracy.
• Create data visualizations and dashboards to communicate insights.
• Stay updated on trends and best practices in data science and AI.

Skills

Data Science

Machine Learning

Predictive Modeling

Python

scikit-learn

Pandas

Communication

Education

Degree in Computer Science, Statistics, Mathematics, Engineering, or related field

Tools

XGBoost

PyTorch

TensorFlow

Docker

AWS

Google Cloud

scikit-learn

Job description

We’re looking for a skilled Data Scientist to join our team. You’ll develop and deploy advanced machine learning models, analyze large datasets, and uncover insights to drive business outcomes. Working closely with cross-functional teams, you’ll identify opportunities, prototype solutions, and deliver scalable models.

Key Responsibilities:

• Develop and deploy machine learning models using tools like scikit-learn, XGBoost, PyTorch, and TensorFlow.
• Analyze datasets to identify trends and patterns that drive business value.
• Collaborate with product managers, engineers, and stakeholders to define and achieve project goals.
• Design experiments, evaluate model performance, and optimize algorithms.
• Implement and optimize data preprocessing, feature engineering, and training pipelines.
• Evaluate external data sources to enhance datasets and improve model accuracy.
• Create data visualizations and dashboards to communicate insights.
• Stay updated on trends and best practices in data science and AI.

Qualifications:

• Degree in Computer Science, Statistics, Mathematics, Engineering, or related field.
• Experience in data science, machine learning, and predictive modeling.
• Proficiency in Python and its data science libraries (e.g., scikit-learn, pandas).
• Experience with machine learning frameworks like XGBoost, PyTorch, TensorFlow.
• Strong understanding of statistical concepts and data preprocessing techniques.
• Excellent problem-solving and communication skills.

Preferred Qualifications:

• Experience deploying models in production environments.
• Familiarity with deep learning and neural networks.
• Knowledge of cloud platforms (e.g., AWS, Google Cloud) and containerization (e.g., Docker).
• Competitive salary, bonuses, and comprehensive insurance.
• Retirement savings plan with matching contributions.
• Flexible schedule and remote work options.
• Professional development and tuition reimbursement.
• Collaborative and inclusive company culture.