OMG Technologies

OMG Technologies

Data Scientist (Hybrid - Raleigh, NC)

Raleigh, North Carolina, USA · Contract

Sponsorship not specifiedDetected 70 days ago
PythonBashAlgorithmsGitSQLPostgreSQLMySQLDynamoDBSnowflakeDatabricksAWSGCPAzureCloud PlatformsCI/CDGitHub ActionsMachine LearningTensorFlowPyTorchscikit-learnPandasAirflowData ScienceA/B Testing

About the role

  • Collaboration & Communication: Work closely with stakeholders to understand business challenges and translate them into data science solutions and work in the end-to-end solutioning.
  • Governance & Risk: Enforce model/version lineage, reproducibility, approvals, rollback plans, auditability, and cost controls aligned to enterprise policies.
  • Hands-on Delivery: Prototype new patterns; troubleshoot production issues across data, model, and infrastructure layers.

Responsibilities

  • Build ML Models: Design and implement predictive and prescriptive models for regression, classification, and optimization problems.Apply advanced techniques such as structural time series modeling and boosting algorithms (e.g., XGBoost, LightGBM).
  • Collaborate with cross-functional teams to ensure successful integration of models into business processes.
  • Monitoring & Visualization: Rapidly prototype and test hypotheses to validate model approaches.
  • Build automated workflows for model monitoring and performance evaluation.
  • Create dashboards using tools like Databricks and Palantir to visualize key model metrics like model drift, Shapley values etc.
  • Productionize ML: Build repeatable paths from experimentation to deployment (batch, streaming, and low-latency endpoints), including feature engineering, training, evaluation, Own ML Platform: Stand up and operate core platform components model registry, feature store, experiment tracking, artifact stores, and standardized CI/CD for ML.
  • Pipeline Engineering: Author robust data/ML pipelines (orchestrated with Step Functions / Airflow / Argo) that train, validate, and release models on schedules or events.
  • Observability & Quality: Implement end-to-end monitoring, data validation, model/drift checks, and alerting SLA/SLOs.
  • Partner & Mentor: Collaborate with on-shore/off-shore teams; coach data scientists on packaging, testing, and performance; contribute to standards and reviews.
  • Design and implement predictive and prescriptive models for regression, classification, and optimization problems.Apply advanced techniques such as structural time series modeling and boosting algorithms (e.g., XGBoost, LightGBM).

Requirements

  • Programming: 5+ years experience with Python (pandas, PySpark, scikit-learn
  • familiarity with PyTorch/TensorFlow helpful), bash, experience with Docker.
  • ML Tooling: 5+ years experience with SageMaker (training, processing, pipelines, model registry, endpoints) or equivalents (Kubeflow, MLflow/Feast, Vertex, Databricks ML).
  • Pipelines & Orchestration: 5+ years experience with Databricks DABS or Airflow or Step Functions, e-driven designs with EventBridge/SQS/Kinesis.
  • Cloud Foundations: 3+ years experience with AWS/Azure/Google Cloud Platform on various services like ECR/ECS, Lambda, API Gateway, S3, Glue/Athena/EMR, RDS/Aurora (PostgreSQL/MySQL), DynamoDB, CloudWatch, IAM, VPC, WAF.
  • CI/CD: 3+ years hands-on experience with CodeBuild/Code Pipeline or GitHub Actions/GitLab
  • Feature Pipelines: Proven experience with batch/stream pipelines, schema management, partitioning, performance tuning
  • Bachelor s degree in Computer Science, Information Technology, Data Science, or related field.
  • 5+ years experience with Python (pandas, PySpark, scikit-learn
  • 5+ years experience with SageMaker (training, processing, pipelines, model registry, endpoints) or equivalents (Kubeflow, MLflow/Feast, Vertex, Databricks ML).

Nice to have

  • Experience in retail/manufacturing is preferred.

Skills

  • Additional Qualification: Experience in retail/manufacturing is preferred.

Benefits

  • Train and Tune Models: Develop and tune machine learning models using Python, PySpark, TensorFlow, and PyTorch.

Company info

  • This position is 4 days in office, 1 day remote per week, based at our corporate headquarters in Raleigh, North Carolina (North Hills).
  • Role Summary We are seeking an experienced Data Scientist with strong expertise in Data Science, machine learning engineering with hands on experience in designing and deploying ML solutions in production.
  • This role focuses on building scalable ML solutions, productionizing models, and enabling robust ML platforms for enterprise-grade deployments.
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This listing is sourced directly from OMG Technologies's careers page and normalized into a canonical job model.