Senior Manager, Data Science (Models)

Horizontal Talent; Houston (TX); Hybrid; USD 110,000 - 150,000; Full time

Job summary

Horizontal Talent is seeking a Data Scientist (Models) in a hybrid Houston, TX role. You will design, build, and train models for forecasting and prediction use cases, collaborate with the lead data scientist, and contribute to model documentation and performance reporting.

You will developML pipelines, perform hyperparameter tuning, and analyze feature importance while leveraging manufacturing or inventory data to inform insights. Strong documentation and communication are essential.

Qualifications

• Experience designing, building, and training forecasting and prediction models.
• Proficient in Python and scikit-learn with hands-on ML development.
• Familiarity with model deployment and experimentation pipelines.

Responsibilities

• Design, build, and train models for forecasting, failure prediction, mix classification, and demand lifecycle analysis.
• Develop and refine ML pipelines for feature engineering and experimentation.
• Run model testing activities including hyperparameter tuning and ablation studies.
• Collaborate with lead data scientist on parallel workstreams to support model development.
• Contribute to model cards, experiment documentation, performance summaries, and accuracy reporting.
• Utilize manufacturing or inventory data to inform modeling approaches.

Skills

ML modeling

Python

scikit-learn

LightGBM

XGBoost

SageMaker

model evaluation

documentation

communication

Tools

LightGBM

XGBoost

SageMaker

Job description

We’re looking for a Data Scientist (Models) to help drive model design and training across several forecasting and prediction use cases in a fast-paced, collaborative environment. This is a hybrid role in Houston, TX, where you’ll contribute hands‑on technical expertise, strong documentation, and thoughtful partnership with the lead data science team.

Responsibilities

• Design, build, and train models for forecasting, failure prediction, mix classification, and demand lifecycle analysis
• Develop and refine machine learning pipelines that support feature engineering and experimentation efforts
• Run model testing activities such as hyperparameter tuning, ablation studies, and feature importance analysis
• Collaborate closely with the lead data scientist on parallel workstreams to support efficient model development
• Contribute to model cards, experiment documentation, performance summaries, and accuracy reporting
• Use manufacturing or inventory-related data when available to inform modeling approaches and insights

Skills

• Strong experience with machine learning modeling, including both classification and regression
• Hands‑on programming experience with Python and scikit‑learn
• Experience using LightGBM and/or XGBoost
• Working knowledge of SageMaker, including training jobs and hyperparameter tuning
• Ability to work effectively under the direction of a lead data scientist
• Strong documentation habits and attention to detail
• Clear communication and a collaborative mindset

Preferred Skills

• Experience with multi‑class classification problems
• Exposure to manufacturing, supply chain, or inventory data
• Background in oil and gas or related operational environments
• Familiarity with demand forecasting or predictive modeling for operational use cases

Horizontal Talent is committed to fostering an inclusive and welcoming hiring process where all candidates are respected and supported. We value diversity, equity, and inclusion as core principles and encourage qualified applicants from all backgrounds to apply.

By applying for this position, you acknowledge and agree that Horizontal Talent may contact you regarding your application using automated technology, including phone calls, SMS/text messages, or email, which may be delivered by our virtual AI recruiter, Alex.