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4P Consulting Inc.
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Data Scientist II 4P/573

4P Consulting Inc. · Atlanta, GA, US

Actively hiring Posted 4 months ago

Responsibilities

  • Collect, clean, and analyze complex datasets
  • Identify trends, patterns, and actionable insights
  • Apply statistical techniques to support data-driven decisions
  • Develop and deploy machine learning models to predict future trends and outcomes
  • Apply regression, clustering, classification, and advanced modeling techniques
  • Build and optimize algorithms such as: Decision Trees Random Forests Neural Networks Gradient Boosting models
  • Decision Trees
  • Random Forests
  • Neural Networks
  • Gradient Boosting models
  • Engineer and select relevant features to improve model performance
  • Fine-tune model parameters and validate predictive accuracy
  • Ensure models are scalable and production-ready
  • Deploy machine learning models into production environments
  • Support real-time decision-making applications
  • Monitor model performance and retrain as needed
  • Develop dashboards and visualizations using Tableau, Power BI, or Python libraries (Matplotlib, Seaborn, etc.)
  • Communicate insights effectively to technical and non-technical stakeholders
  • Design and analyze A/B tests
  • Conduct hypothesis testing and provide statistical validation
  • Measure business impact of changes and enhancements
  • Collaborate with IT and database teams to access and integrate data sources
  • Work with cross-functional teams (engineering, business analysts, domain experts)
  • Align data science initiatives with strategic business objectives
  • Ensure ethical data practices and compliance with data privacy regulations
  • Maintain documentation and transparency in model development
  • Mentor junior data scientists and analysts
  • Contribute to best practices and data science methodologies
  • Stay current with emerging tools, technologies, and industry trends

Basic qualifications

  • Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or related quantitative field
  • 5–10 years of experience in data science, machine learning, and statistical analysis
  • Proficiency in Python, R, or Julia
  • Strong understanding of machine learning algorithms and their applications
  • Experience with SQL and database querying
  • Experience with data visualization tools (Tableau, Power BI, or Python libraries)
  • Strong analytical, problem-solving, and critical-thinking skills
  • Excellent written and verbal communication skills

Preferred qualifications

  • Master’s or Ph.D. in a quantitative field
  • Experience with big data technologies (Hadoop, Spark)
  • Experience with distributed computing frameworks
  • Experience deploying models in cloud environments

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