AdvanceAuto Parts
AdvanceAuto Parts

Data Scientist

Raleigh, NC, US • Posted 3 days ago • Updated 3 hours ago
Full Time
On-site
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Business Process
  • Visualization
  • Workflow
  • Performance Appraisal
  • Streaming
  • Evaluation
  • Data Validation
  • SLA
  • Mentorship
  • Collaboration
  • Computer Science
  • Information Technology
  • Data Science
  • Mathematics
  • Statistics
  • Python
  • Pandas
  • PySpark
  • scikit-learn
  • PyTorch
  • TensorFlow
  • Bash
  • Docker
  • Regression Analysis
  • Optimization
  • Time Series
  • Modeling
  • Algorithms
  • XGBoost
  • Amazon SageMaker
  • Vertex
  • Machine Learning (ML)
  • Orchestration
  • Databricks
  • Step-Functions
  • Amazon SQS
  • Amazon Kinesis
  • Cloud Computing
  • Amazon Web Services
  • Microsoft Azure
  • API
  • Amazon S3
  • Electronic Health Record (EHR)
  • Remote Desktop Services
  • Amazon RDS
  • PostgreSQL
  • MySQL
  • Amazon DynamoDB
  • Virtual Private Cloud
  • WAF
  • Google Cloud
  • Google Cloud Platform
  • Database
  • Snow Flake Schema
  • SQL
  • RBAC
  • UDF
  • Continuous Integration
  • Continuous Delivery
  • GitHub
  • GitLab
  • Management
  • Performance Tuning
  • Apache Parquet
  • Testing
  • Training
  • Performance Monitoring
  • Incident Management
  • Dashboard
  • Debugging
  • Data Modeling
  • Soft Skills
  • Communication
  • SAP BASIS
  • Privacy

Summary

Job Description

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.

This role is a hybrid work model (4 days in office, 1 day work from home) based out of our corporate headquarters located in Raleigh, NC

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 Mathematics, Statistics or related field. MS Preferred.
  • 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. Google Cloud Platform experience is preferred.
  • 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.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age national origin, religion, sexual orientation, gender identity, status as a veteran and basis of disability or any other federal, state or local protected class. We comply with all applicable federal, state, and local laws.

California Residents click below for Privacy Notice:

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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: 10110493
  • Position Id: 45b4d195363b8fd98acb76d06da0c92e
  • Posted 3 days ago
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