Senior Data Scientist - Machine Learning

Xforia Global Talent & Technology Solutions; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

Xforia Global Talent & Technology Solutions seeks a Senior Data Scientist to join a centralized ML team in the United States. You will own productionizing ML models and pipelines end-to-end, collaborating across data science, engineering, and product to deliver production-ready solutions that impact revenue.

The role emphasizes deployment, monitoring, and optimization on cloud platforms such as Databricks and Azure, with strong Python coding and production-grade practices required.

Qualifications

• 3+ years of professional experience in a technical environment.
• Strong Python expertise with production-grade coding, modularization, testing, and performance tuning.
• Hands-on ML pipeline experience including deployment, orchestration, monitoring, and optimization.
• Solid knowledge of statistical and machine learning techniques.
• Experience with data extraction, cleaning, and analysis.
• Excellent verbal and written communication skills.

Responsibilities

• Take ownership of productionizing ML pipelines, including refactoring and optimizing for performance.
• Design, build, deploy, and monitor ML models in a production environment.
• Collaborate with data scientists and engineers to embed ML solutions in business apps.
• Improve and maintain existing codebases with quality, modularity, and testing.
• Partner with stakeholders to translate business needs into scalable ML solutions.
• Communicate complex results to technical and non-technical audiences.

Skills

Python

ML pipelines

Statistics

Data extraction

Communication

SQL

Databricks

Spark

CI/CD

Model monitoring

Azure

AWS

GCP

Tableau

Power BI

Tools

MLflow

CI/CD

Databricks

Spark

Job description

Note: This is fulltime role, please don't submit candidate on c2c.

We are seeking a highly skilled Senior Data Scientist to join a dynamic, centralized Machine Learning team supporting seven key business units. This is a crucial role focused on taking cutting-edge ML models from prototype to production, directly contributing to measurable revenue impact.

You will be responsible for the end-to-end lifecycle of machine learning models, with a strong emphasis on productionization, system integration, and optimization. The ideal candidate is an expert Python developer with hands-on experience deploying and monitoring scalable ML pipelines on cloud platforms like Databricks and Azure. You will collaborate closely with data scientists, engineers, and product partners to accelerate the delivery of robust, production-ready ML solutions that drive business value.

Key Responsibilities

• Take ownership of productionizing ML pipelines, including refactoring existing code and optimizing systems for performance and scalability.
• Design, build, deploy, and monitor machine learning models in a production environment.
• Collaborate with a high-performing team of data scientists and engineers to embed ML solutions into business-critical applications.
• Improve and maintain existing codebases, ensuring code quality, modularity, and rigorous testing.
• Partner with stakeholders to understand business needs and translate them into scalable ML solutions, particularly for the Customer Intelligence CBI productionization initiative.
• Communicate complex technical concepts and results to both technical and non-technical audiences across all levels of the organization.

Required Qualifications

• 3+ years of professional experience in a technical environment.
• Strong Python Expertise: Proven experience with production-grade coding, modularization, testing, and performance tuning.
• Hands-on ML Pipeline Experience: Demonstrated experience with the full ML lifecycle, including model deployment, orchestration, monitoring, and optimization.
• Solid depth of knowledge in statistical and machine learning techniques.
• Practical experience with data extraction, cleaning, and analysis.
• Excellent verbal and written communication skills, with the ability to collaborate effectively within a diverse team.

Preferred Qualifications

• 8+ years of experience in a technical professional environment.
• Experience with Databricks and/or Spark-based ML pipelines.
• Proficiency in SQL and experience working with large-scale datasets.
• Experience with ML lifecycle tools (e.g., MLflow, CI/CD, model monitoring).
• Experience in using cloud platforms (e.g., Azure, AWS, GCP) and parallel processing to scale model development and deployment.
• Practical experience with data visualization tools (e.g., Tableau, PowerBI).
• Domain knowledge in the airline industry is a plus.
• Experience working in a consulting role or a centralized ML team.