Technology - Data Scientist

Hybrid in Raleigh, NC, US • Posted 2 hours ago • Updated 2 hours ago
Contract W2
Contract Independent
No Travel Required
Hybrid
$55 - $60/hr
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Fitment

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Job Details

Skills

  • Python
  • Time Series
  • PyTorch
  • TensorFlow
  • Google Cloud Platform
  • Amazon Web Services
  • XGBoost

Summary

Must have: Python & Pyspark experience
Preferred: AWS, Google Cloud Platform or other machine learning certifications
Preferred: XGBoos, Timeseries, Pytorch, or Tensorflow experience

Remote or On-site: This position is 4 days in office, 1 day remote per week, based at our corporate headquarters in Raleigh, North Carolina (North Hills) Time Zone Requirements.
Interview Process: MS Teams interviews.

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Data Scientist
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.
 
Key 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).
  • Train and Tune Models: Develop and tune machine learning models using Python, PySpark, TensorFlow, and PyTorch.
  • 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. 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.
  • Governance & Risk: Enforce model/version lineage, reproducibility, approvals, rollback plans, auditability, and cost controls aligned to enterprise policies.
  • Partner & Mentor: Collaborate with on-shore/off-shore teams; coach data scientists on packaging, testing, and performance; contribute to standards and reviews.
  • Hands-on Delivery: Prototype new patterns; troubleshoot production issues across data, model, and infrastructure layers

 

Required Qualifications
  • Education: Bachelor’s degree in Computer Science, Information Technology, Data Science, or related field.
  • Programming: 5+ years experience with Python (pandas, PySpark, scikit-learn; familiarity with PyTorch/TensorFlow helpful), bash, experience with Docker.
  • ML Experimentation: 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).
  • 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.
  • Snowflake Foundations: Warehouses, databases, schemas, stages, Snowflake SQL, RBAC, UDF, Snowpark.
  • CI/CD: 3+ years hands-on experience with CodeBuild/Code Pipeline or GitHub Actions/GitLab; blue/green, canary, and shadow deployments for models and services.
  • Feature Pipelines: Proven experience with batch/stream pipelines, schema management, partitioning, performance tuning; parquet/iceberg best practices.
  • Testing & Monitoring: Unit/integration tests for data and models, contract tests for features, reproducible training; data drift/performance monitoring.
  • Operational Mindset: Incident response for model services, SLOs, dashboards, runbooks; strong debugging across data, model, and infra layers.
  • Soft Skills: Clear communication, collaborative mindset, and a bias to automate & document.
Additional Qualification:
  • Experience in retail/manufacturing is preferred.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 91171293
  • Position Id: 8965996
  • Posted 2 hours ago

Company Info

About G3 Business Services LLC

At G3 Business Services, we offer a variety of innovative IT solutions suitable for various industries, and for companies of all sizes. We are well-versed in modernizing IT platforms, digital transformation, Cloud migration, AI,  and Security and protection. We work with just about any technology that a business would encounter. We believe in long-term partnerships, and our services are therefore designed around the specific needs of our clients. We work hard - so our clients can sleep at night, knowing that their IT operations are taken care of in the most professional way.

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