Data Scientist

Relha LLC; Northern (KY); Hybrid; USD 110,000 - 117,000; Full time

Job summary

The role involves building models that deliver measurable business value, optimizing data models, and collaborating with stakeholders to align with objectives. Opportunities exist to work with Palantir Foundry, Google Cloud, and modern BI tooling.

Qualifications

• Proficiency in Python, PySpark, and SQL for data analysis, feature engineering, and model development.
• Expertise in time series forecasting models and ML-based approaches.
• Hands-on data engineering experience with ETL and data transformations.

Responsibilities

• Develop and optimize machine learning models with a focus on time series forecasting and predictive analytics.
• Build and optimize features and data models to improve accuracy and efficiency.
• Evaluate model performance using metrics like MAPE, RMSE, R² and adjust strategies accordingly.
• Create data pipelines using PySpark, SQL, and cloud-based solutions for seamless data integration.
• Work on large-scale data integration projects using Boomi, SnapLogic, SSIS, or Palantir to extract, transform, and load data.
• Utilize Palantir Foundry, Google Cloud, AutoAI, and Google Colab for data modeling, processing, and automation.
• Design and maintain data warehouse solutions to support analytics and BI.
• Perform complex data transformations to support AI/ML initiatives.
• Collaborate with stakeholders to ensure models align with business objectives.
• Deploy, monitor, and improve ML models in production environments.
• Communicate findings clearly to technical and non-technical audiences.

Skills

Python

PySpark

SQL

Time series forecasting

Feature engineering

Data pipelines

Production ML models

Tools

Boomi

SnapLogic

SSIS

Palantir Foundry

Job description

Owens & Minor is a global healthcare solutions company providing essential products, services and technology solutions that support care delivery in leading hospitals, health systems and research centers around the world. For over 140 years, Owens & Minor has delivered comfort and confidence behind the scenes, so healthcare stays at the forefront, helping to make each day better for the hospitals, healthcare partners, and communities we serve. Powered by more than 14,000 teammates worldwide, Owens & Minor exists because every day, everywhere,Life Takes Care™.

Global Reach with a Local Touch

140+ years serving healthcare

Over 14,000 teammates worldwide

Serving healthcare partners in 80 countries

Manufacturing facilities in the U.S., Honduras, Mexico, Thailand and Ireland

Portfolio of 300 propriety and branded product offerings

1,000 branded medical product suppliers

Comprehensive Healthcare Plan-Medical, dental, and vision plans start on day one of employment for full-time teammates.

Educational Assistance-We offer educationalassistanceto all eligible teammates enrolled in an approved, accredited collegiate program.

Employer-Paid Life Insurance and Disability-We offer employer-paid life insurance and disabilitycoverage.

Voluntary Supplemental Programs – We offer additional options to secure your financial future including supplemental life, hospitalization, critical illness, and other insurance programs.

Support for your Growing Family – Adoption assistance, fertility benefits (in medical plan) and parental leave are available for teammates planning for a family.

Health Savings Account (HSA)and401(k)-We offer these voluntary financial programs to help teammates prepare for their future, as well as other voluntary benefits.

Paid Leave-In addition to sick days and short-term leave, we offer holidays, vacation days, personal days, andadditionaltypes of leave – including parental leave.

Well-Being – Also included in our offering is a Teammate Assistance Program (TAP), Calm Health, Cancer Resources Services, and discount programs – all at no cost to you.

The anticipated salary range for this position is $110,000- $117,000 USD Annual. The actual compensation offered may vary based on job related factors such as experience, skills, education and location

Job Description:

We are seeking a highly skilled Data Scientist with a strong background in machine learning, data engineering, and model optimization. The ideal candidate should be proficient in Python, PySpark, and SQL, experienced in time series forecasting, feature engineering, and data model performance evaluation, and capable of working with large-scale data integration projects across various domains.

A large part of this role involves building machine learning models that not only meet but exceed user expectations, driving measurable value for the business. The candidate will need to have a strong grasp of data model optimization, feature engineering, and model evaluation metrics to ensure high-performance solutions.

Key Responsibilities:

• Develop and optimize machine learning models with a focus on time series forecasting and predictive analytics.
• Perform feature engineering and data model optimization to enhance model accuracy and efficiency.
• Continuously evaluate model performance using metrics such as MAPE, RMSE, R², and adjust strategies accordingly.
• Build and implement data pipelines using PySpark, SQL, and cloud-based solutions for seamless data integration.
• Work on large-scale data integration projects, leveraging tools such as Boomi, SnapLogic, SSIS, or Palantir to extract, transform, and load data.
• Utilize Palantir Foundry, Google Cloud, AutoAI, and Google Colab for data modeling, processing, and automation.
• Design and maintain data warehouse solutions to support advanced analytics and business intelligence.
• Perform complex data transformations using SQL queries and data objects to support AI/ML-driven initiatives.
• Collaborate closely with business stakeholders to ensure models align with user expectations and business objectives.
• Deploy, monitor, and continuously improve machine learning models in production environments.
• Communicate technical findings and insights effectively to both technical and non-technical audiences.

Required Skills & Qualifications:

• Proficiency in Python, PySpark, and SQL for data analysis, feature engineering, and model development.
• Expertise in time series forecasting models, including ARIMA, Prophet, LSTMs, and ML-based approaches.
• Strong experience in data model optimization, feature engineering, and performance evaluation.
• Deep understanding of ML model evaluation metrics and best practices in improving model accuracy.
• Hands-on experience in data engineering, working on data pipelines, ETL, and data transformation projects.
• Experience using Boomi, SnapLogic, SSIS, or Palantir for data integration.
• Proficiency in cloud computing, particularly Google Cloud (BigQuery, Vertex AI, Cloud Functions, etc.).
• Experience with Palantir Foundry for data processing, analysis, and visualization.
• Ability to optimize and query large-scale datasets using data lakes and relational databases.
• Familiarity with AutoAI for automated model selection and hyperparameter tuning.
• Experience with Google Colab for collaborative machine learning development.
• Excellent problem-solving and communication skills, with the ability to convey complex concepts to business stakeholders.

Preferred Qualifications:

• Experience with MLOps for continuous deployment, monitoring, and retraining of ML models.
• Knowledge of business intelligence and reporting tools for data visualization.
• Background in supply chain, logistics, or operational forecasting.
• Experience in both batch and real-time data processing architectures.
• Ability to optimize SQL queries and data transformations for performance improvements.

If you feel this opportunity could be the next step in your career, we encourage you to apply. This position will accept applications on an ongoing basis.

Owens & Minor is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, national origin, sex, sexual orientation, genetic information, religion, disability, age, status as a veteran, or any other status prohibited by applicable national, federal, state or local law.