Resolution Technologies is seeking a Senior Data Scientist for a long-term pharma industry engagement onsite in Atlanta, GA. This benefits-forward role sits inside the client’s data and AI team, offering hands-on ownership of end-to-end ML initiatives, from modeling to data pipelines and MLOps across the full lifecycle.

Responsibilities

Design, train, and validate production-grade ML models to support predictive analytics use cases such as batch/resource optimization and anomaly detection in a manufacturing setting.
Develop and maintain data transformation and cleanup pipelines in Snowflake to produce modeling-ready datasets.
Automate ingestion and processing of new and recurring data feeds, including data arriving from external systems or partners with latency.
Own the full ML lifecycle in AWS SageMaker or Snowflake-native ML where appropriate: training, deployment, monitoring, retraining, and drift detection.
Implement MLOps practices: CI/CD for ML, model versioning, automated pipelines, and performance monitoring.
Evaluate the client’s existing environment, including Snowflake native MLOps capabilities, and recommend a cost-effective, fit-for-purpose path before building from scratch.
Contribute to a blueprint for the client’s ML operating model: where models are trained, how they are promoted and deployed, and how users access outputs (dashboards or batch inputs).
Collaborate with stakeholders to translate business requirements into production solutions and deliver work in phases, focusing on high-value, low-effort use cases first.

Requirements

Proven experience building and deploying ML models in production.
Strong Python skills and ML libraries (scikit-learn, XGBoost, TensorFlow, or PyTorch).
Solid data engineering capabilities: SQL, data transformation, and pipeline development (dbt, Snowflake-native, or equivalent).
Hands-on Snowflake experience for warehousing, transformation, and ingestion.
Hands-on AWS SageMaker experience across the model lifecycle.
Experience with MLOps tooling: CI/CD for ML, monitoring, automated retraining, and version control.
Ability to work independently and reliably in a staff augmentation capacity as part of the client’s team.

Technologies

Snowflake
AWS SageMaker
Python
scikit-learn
XGBoost
TensorFlow
PyTorch
dbt
Snowflake-native ML
Airflow
Step Functions
Terraform
CloudFormation
Docker
SQL

About the Role

The client is looking for a Senior Data Scientist for a long-term engagement with a pharmaceutical client. This is a hands-on, end-to-end role embedded directly within the client’s data and AI team. The data scientist will build machine learning models and predictive analytics solutions and own the data engineering behind them—including transformation, cleanup, and automated ingestion of new data—as well as the full MLOps lifecycle. The client is establishing its production ML capability.

What Sets a Strong Sr. Data Scientist Candidate Apart

We value candor about capability. The client seeks someone whose experience aligns with their resume, who can assess the landscape, make sound technical judgments, and adapt to new areas such as agentic or generative AI as the engagement matures. The ideal candidate can build production ML solutions while helping mature the surrounding framework.