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Xgboost Jobs (NOW HIRING)

Steampunk

Data Scientist

Mclean, VA · On-site

$125K - $160K/yr

Develop machine learning models using frameworks such as scikit-learn, XGBoost, PyTorch, TensorFlow, or similar libraries. * Perform feature engineering, dataset preparation, and model optimization ...

Steampunk

Data Scientist

Mclean, VA · On-site

$125K - $160K/yr

Develop machine learning models using frameworks such as scikit-learn, XGBoost, PyTorch, TensorFlow, or similar libraries. * Perform feature engineering, dataset preparation, and model optimization ...

Steampunk

Data Scientist

Mclean, VA

$125K - $160K/yr

Develop machine learning models using frameworks such as scikit-learn, XGBoost, PyTorch, TensorFlow, or similar libraries. * Perform feature engineering, dataset preparation, and model optimization ...

Tror AI for everyone

MLOPS Engineer

Concord, CA · On-site

Strong proficiency in Java and Python , SQL, and ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch). * Experience with cloud platforms and containerization (Docker, Kubernetes). * Hands ...

Steampunk

Data Scientist

Mclean, VA · On-site

$125K - $160K/yr

Develop machine learning models using frameworks such as scikit-learn, XGBoost, PyTorch, TensorFlow, or similar libraries. * Perform feature engineering, dataset preparation, and model optimization ...

CarGurus

Machine Learning Operations Engineer

Boston, MA · On-site

$124K - $149K/yr

Python ML ecosystem, such as scikit-learn, XGBoost, PyTorch, numpy, or pandas; Deploying, monitoring, and troubleshooting ML models in public cloud platforms, such as AWS; and SQL and cloud data ...

Pattern AI

Machine Learning Engineer

San Mateo, CA

Broad familiarity with the Python ecosystem and common libraries including Scikit-Learn, XGBoost, PyTorch, Keras, Tensorflow, Pandas, and common ML cloud services. * Familiarity with CNNs, RNN, LSTMs ...

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site +1

Broad familiarity with the Python ecosystem and common libraries including Scikit-Learn, XGBoost, PyTorch, Keras, Tensorflow, Pandas, and common ML cloud services. * Familiarity with CNNs, RNN, LSTMs ...

OKX

Sr Data Scientist, Risk Strategy

San Jose, CA · Hybrid

$223K - $268K/yr

Deep understanding of modern machine learning techniques / algorithms including GBM, XGBoost, LGBM, etc. Advanced programming skills of statistical / analytical software (SQL, R, Python,etc.

Experian

$81K - $107K/yr

Experience with regression, XGBoost, and other core ML algorithms. * Hands-on experience across the full model lifecycle: data ingestion, EDA, modeling, validation, and deployment. * Experience ...

New

OKX

Sr Data Scientist, Risk Strategy

San Jose, CA · On-site

$223K - $268K/yr

Deep understanding of modern machine learning techniques / algorithms including GBM, XGBoost, LGBM, etc. Advanced programming skills of statistical / analytical software (SQL, R, Python,etc.

Advance Auto Parts

Data Scientist

Raleigh, NC · On-site +1

Apply advanced techniques such as structural time series modeling and boosting algorithms (e.g., XGBoost, LightGBM). * Train and Tune Models: Develop and tune machine learning models using Python ...

EchoStar

Senior Data Scientist

Littleton, CO · On-site

$141K/yr

Python, R, Scala, SQL, PySpark, TensorFlow, PyTorch, Keras, scikit-learn, MLflow, LangChain, XGBoost, LightGBM, CatBoost, and Prophet. * AWS (S3, EC2, Glue, Lambda, SageMaker, Bedrock), Snowflake ...

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How much do xgboost jobs pay per hour?

As of Jun 19, 2026, the average hourly pay for xgboost in the United States is $36.26, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $39.66 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer specializing in XGBoost, and why are they important?

To thrive as a Machine Learning Engineer specializing in XGBoost, you need a strong background in statistics, data analysis, and programming (especially Python), often supported by a degree in computer science or a related field. Proficiency with XGBoost, data preprocessing libraries (like pandas and NumPy), and experience with machine learning platforms such as scikit-learn or TensorFlow are typically required. Analytical thinking, problem-solving, and effective communication are essential soft skills for interpreting results and collaborating with stakeholders. These skills ensure accurate model development, efficient implementation, and impactful business outcomes from machine learning projects.

What is XGBoost?

XGBoost stands for eXtreme Gradient Boosting and is an open-source machine learning library that provides an efficient and scalable implementation of gradient boosting algorithms. It is commonly used for supervised learning tasks, such as classification and regression, due to its high performance, speed, and ability to handle missing values. XGBoost supports parallel processing, regularization to prevent overfitting, and can be used with various programming languages like Python, R, and Julia. Its popularity stems from its success in many machine learning competitions and real-world applications.

What types of projects or datasets do professionals commonly work with when using XGBoost in a machine learning role?

Professionals using XGBoost often tackle projects involving structured data, such as customer analytics, credit scoring, fraud detection, and sales forecasting. XGBoost is particularly valued for its speed and accuracy with large tabular datasets, making it a popular choice in finance, healthcare, and e-commerce. On a daily basis, you may collaborate with data engineers to preprocess data, work with data scientists to tune hyperparameters, and communicate findings to business stakeholders. The role typically involves iterating on feature engineering, model evaluation, and integrating models into production pipelines.

What is the difference between Xgboost vs Data Scientist?

AspectXgboostData Scientist
Primary RoleDeveloping and tuning machine learning models, especially gradient boosting algorithmsAnalyzing data, building models, and deriving insights across various techniques
Required SkillsProgramming (Python, R), machine learning, data preprocessingStatistics, programming, data visualization, machine learning
Work EnvironmentData science teams, machine learning projects, software developmentResearch, data analysis, cross-functional collaboration

While Xgboost is a specific machine learning algorithm used within data science projects, a Data Scientist encompasses a broader role involving data analysis, modeling, and insights. Xgboost is a tool often employed by Data Scientists to improve predictive performance, but the Data Scientist's responsibilities extend beyond just implementing algorithms.

What is the highest paid job in data science?

In data science, senior roles such as Lead Data Scientist, Machine Learning Engineer, or Data Science Director tend to have the highest salaries, often exceeding six figures annually. These positions typically require advanced skills in machine learning, statistical analysis, and experience with tools like XGBoost, along with leadership responsibilities.

Is XGBoost better than linear regression?

XGBoost is a powerful machine learning algorithm that often outperforms linear regression in predictive accuracy, especially with complex, non-linear data. However, linear regression is simpler, more interpretable, and suitable for problems with linear relationships, making the choice dependent on the specific task and data characteristics in a data science or machine learning role.

Is XGBoost considered AI?

XGBoost is a machine learning algorithm used for classification and regression tasks, often employed by data scientists and machine learning engineers. While it is a tool within artificial intelligence applications, XGBoost itself is not considered AI but a method used to develop AI models. Knowledge of programming languages like Python or R and understanding of data preprocessing are important for roles involving XGBoost.

What does XGBoost stand for?

XGBoost is an open-source machine learning library that implements gradient boosting algorithms, commonly used for structured data prediction tasks. The name stands for eXtreme Gradient Boosting, highlighting its focus on high-performance gradient boosting techniques often utilized by data scientists and machine learning engineers.
More about Xgboost jobs
What job categories do people searching Xgboost jobs look for? The top searched job categories for Xgboost jobs are:
Xgboost jobs near you
Infographic showing various Xgboost job openings in the United States as of June 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% In-person job distribution, with an average salary of $75,411 per year, or $36.3 per hour.

Data Scientist

Steampunk

Mclean, VA • On-site

$125K - $160K/yr

Other

Posted 4 days ago

Job description

Overview
We are seeking aData Scientist to design, build, and deliver predictive analytics, machine learning models, and data-driven insights that support mission and business outcomes. This role requires strong analytical and modeling skills, hands-on experience with ML frameworks, and the ability to collaborate across engineering, data, and product teams. The Data Scientist will contribute to the full lifecycle of model development, from data exploration and feature engineering to model training, evaluation, and deployment, while supporting the articulation of insights and recommendations to technical and non-technical stakeholders.
Contributions
  • Conduct exploratory data analysis (EDA) to uncover trends, identify data quality issues, and determine modeling opportunities.
  • Develop machine learning models using frameworks such as scikit-learn, XGBoost, PyTorch, TensorFlow, or similar libraries.
  • Perform feature engineering, dataset preparation, and model optimization to improve predictive accuracy and operational performance.
  • Evaluate models using appropriate statistical methods and performance metrics, documenting findings and informing iterative improvements.
  • Work with Data Engineers to understand and enhance data pipelines, ensuring model-ready datasets are accurate, complete, and consistent.
  • Collaborate with AI Developers and LLMOps/MLOps Engineers to integrate ML models into production environments or decision-support applications.
  • Build visualizations, dashboards, data stories, and executive-friendly summaries to communicate insights clearly to stakeholders.
  • Support human-centered design processes by translating user needs into modeling requirements and refining model outputs based on feedback.
  • Contribute to reproducibility and auditability by maintaining well-organized code, notebooks, documentation, and experiment histories.
  • Stay current with modern data science methodologies, ML techniques, data processing tools, and cloud-enabled analytics workflows.
  • You will contribute to the growth of our AI & Data Exploitation Practice!

Qualifications
  • Ability to hold a position of public trust with the U.S. government.
  • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Analytics, Engineering, Economics, or a related field.
  • 6+ years of experience building and evaluating machine learning models or performing advanced analytics.
  • Proficiency in Python and core data science libraries (Pandas, NumPy, scikit-learn, Matplotlib/Seaborn).
  • Hands-on experience with at least one modern ML framework (e.g., PyTorch, TensorFlow, XGBoost).
  • Experience writing efficient SQL queries and working with structured or semi-structured data in cloud or database environments.
  • Familiarity with cloud data and ML platforms such as AWS, Azure, GCP, or Databricks.
  • Strong understanding of statistics, probability, experimental design, and model validation techniques.
  • Ability to communicate technical concepts clearly to stakeholders and collaborate across multidisciplinary teams.
  • Experience with dashboarding tools (Tableau, Power BI) or Python visualization libraries is a plus.
  • Curiosity and adaptability, with a drive to stay current in rapidly evolving data and ML practices.
  • Relevant certifications (helpful but not required): Databricks Data Scientist Associate, AWS ML Specialty, Azure Data Scientist Associate, Google Professional Data Engineer.

About steampunk
Steampunk relies on several factors to determine salary, including but not limited to geographic location, contractual requirements, education, knowledge, skills, competencies, and experience. The projected compensation range for this position is $125,000 to $160,000. The estimate displayed represents a typical annual salary range for this position. Annual salary is just one aspect of Steampunk's total compensation package for employees. Learn more about additional Steampunk benefits here.
Identity Statement
As part of the application process, you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.
Steampunk is a Change Agent in the Federal contracting industry, bringing new thinking to clients in the Homeland, Federal Civilian, Health and DoD sectors. Through our Human-Centered delivery methodology, we are fundamentally changing the expectations our Federal clients have for true shared accountability in solving their toughest mission challenges. As an employee owned company, we focus on investing in our employees to enable them to do the greatest work of their careers - and rewarding them for outstanding contributions to our growth. If you want to learn more about our story, visit http://www.steampunk.com.

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