Data Scientist

ZealHire Inc.; Fort Worth (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

ZealHire Inc. is seeking a Senior Machine Learning Engineer/Data Scientist to advance ML models from prototype to production within a centralized ML team. You will optimize performance, refactor code, and build scalable solutions for customer intelligence initiatives in a production environment.

The role emphasizes strong Python skills, end-to-end ML lifecycle expertise, and deployment/monitoring of models in cloud or Databricks settings. On-site in Fort Worth, TX with a 6–12+ month contract.

Qualifications

• Master’s or PhD in Data Science, Computer Science, Statistics, Applied Mathematics, ML or related field.
• At least 3 years of relevant professional experience.
• Strong hands-on experience with Python programming.
• Experience writing modular, testable, production‑grade code.
• Practical experience with data extraction, cleaning, transformation, and analysis.
• Strong understanding of statistical and machine learning techniques.
• Hands-on experience developing and productionizing machine learning pipelines.
• 8+ years of experience in a technical professional environment.
• Experience with Databricks and Spark‑based ML pipelines.
• Experience deploying ML models to production environments.
• Experience with ML lifecycle tools such as MLflow, CI/CD pipelines, and model‑monitoring platforms.
• Experience with Azure or other cloud platforms.
• Experience with parallel processing and distributed computing.
• Experience creating dashboards or data visualizations using Tableau or Power BI.

Responsibilities

• Develop, refactor, test, and optimize production‑quality Python code for ML applications.
• Design, build, deploy, and maintain ML models and pipelines.
• Productionize ML workflows: deployment, orchestration, monitoring, optimization, and troubleshooting.
• Extract, clean, transform, and analyze large datasets to support BI initiatives.
• Apply statistical methods and feature engineering to improve model performance.
• Collaborate with data scientists, data engineers, product partners, and stakeholders to deliver scalable ML solutions.
• Improve existing codebases, pipelines, and system integrations for reliability and performance.
• Debug issues and tune performance across the ML lifecycle.
• Leverage cloud platforms and parallel‑processing tech to scale model development.
• Document solutions and communicate findings clearly to technical and non‑technical audiences.
• Support quality, scalability, and measurable business impact across the org.

Skills

Python programming

Production-grade code

ML lifecycle

Data extraction

Data cleaning

Data transformation

Statistical methods

ML pipelines

Cloud platforms

Education

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

Tools

Databricks

Spark-based ML pipelines

MLflow

CI/CD pipelines

Model monitoring platforms

Tableau/Power BI

Azure or other cloud

Job description

Location: 4700 American Boulevard Fort Worth, TX 76155 (5 days onsite) need local with verified location

Durations: 6-12+ Months with possible extension and conversions.

Interview Process: Two rounds – first virtual, second onsite

want someone who can go for F2F interview

Job Overview:

Our client is seeking a Senior Machine Learning Engineer/Data Scientist to join a centralized Machine Learning team supporting multiple business units. This role will focus on taking machine learning models and pipelines from prototype to production, improving existing codebases, optimizing performance, and building scalable ML solutions for the Customer Intelligence CBI productionization initiative.

The ideal candidate will have strong production-grade Python experience, hands‑on expertise with the complete machine learning lifecycle, and experience deploying and monitoring models in cloud or Databricks environments

Required:

• Master’s or PhD degree in Data Science, Computer Science, Statistics, Applied Mathematics, Machine Learning, or a related quantitative field.
• At least 3 years of relevant professional experience.
• Strong hands‑on experience with Python programming.
• Experience writing modular, testable, maintainable, and production‑grade code.
• Practical experience with data extraction, cleaning, transformation, and analysis.
• Strong understanding of statistical and machine learning techniques.
• Hands‑on experience developing and productionizing machine learning pipelines.

Preferred:

• 8+ years of experience in a technical professional environment.
• Experience with Databricks and Spark‑based machine learning pipelines.
• Experience deploying machine learning models to production environments.
• Experience with ML orchestration, monitoring, and optimization.
• Knowledge of SQL and experience working with large‑scale datasets.
• Experience with ML lifecycle tools such as MLflow, CI/CD pipelines, and model‑monitoring platforms.
• Experience with Azure or other cloud platforms.
• Experience with parallel processing and distributed computing.
• Experience creating dashboards or data visualizations using Tableau or Power BI.
• Airline or transportation industry experience.

Responsibilities:

• Develop, refactor, test, and optimize production‑quality Python code for machine learning applications.
• Design, build, deploy, and maintain machine learning models and pipelines.
• Productionize ML workflows, including model deployment, orchestration, monitoring, optimization, and troubleshooting.
• Extract, clean, transform, and analyze large datasets to support business and customer intelligence initiatives.
• Apply statistical methods, machine learning techniques, and feature engineering to improve model performance.
• Work with data scientists, data engineers, product partners, and business stakeholders to deliver scalable ML solutions.
• Improve existing codebases, pipelines, and system integrations for reliability, maintainability, and performance.
• Debug technical issues and conduct performance tuning across the ML lifecycle.
• Use cloud platforms and parallel‑processing technologies to scale model development and deployment.
• Document technical solutions and communicate findings clearly to both technical and non‑technical audiences.
• Support quality, innovation, scalability, and measurable business or revenue impact across the organization.

$000,000 – $000,000 Salary range is not shown on the candidate portal