Data Scientist - Time Series & ML Engineer

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

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.