Data Scientist II - Digital Foundry

District Of Columbia, United States

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Carrier

Carrier is the global leader in sustainable healthy buildings, HVAC, commercial and transport refrigeration solutions. Learn more about Carrier Corporation.

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Carrier is the leading global provider of healthy, safe and sustainable building and cold chain solutions with a world-class, diverse workforce with business segments covering HVAC, refrigeration, and fire and security. We make modern life possible by delivering safer, smarter and more sustainable services that make a difference to people and our planet while revolutionizing industry trends. This is why we come to work every day. Join us and we can make a difference together.

About this role

The Data Scientist II will work with a multi-disciplinary team to develop high-priority Machine Learning-enabled product features that improve the lives of our customers. The individual will work across a broad portfolio of Carrier digital products, including Abound Health and Sustainability, a cloud-native platform that unlocks siloed building data to create smarter and more resilient spaces that improve occupant and global wellness – and Abound HVAC Performance, a cloud-native application that intelligently monitors connected HVAC systems, providing vital information through a centralized data stream and improved visibility for facility managers.

Key Responsibilities

  • Conduct exploratory data analysis (EDA) to understand data patterns, trends, and relationships.
  • Develop and apply machine learning models and algorithms to solve business problems and extract insights from data.
  • Collaborate with domain experts and stakeholders to define problem statements, data requirements, and success metrics.
  • Clean, preprocess, and transform data to ensure its suitability for analysis and modeling.
  • Conduct statistical analysis and hypothesis testing to validate models and draw meaningful
  • conclusions.
  • Optimize and fine-tune models for accuracy, performance, and scalability.
  • Communicate findings, insights, and recommendations to non-technical stakeholders through data visualizations, reports, and presentations.
  • Stay updated with the latest developments in the field of data science, machine learning, and relevant technologies.

Basic Qualifications

  • Bachelor's degree
  • 3+ months of internship experience in Data Science

Preferred Qualifications

Other qualifications you may have that would be beneficial in this role include:

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
  • Ability to work with large datasets and cloud-based environments (e.g., AWS, Azure, GCP).
  • Excellent problem-solving skills and a proactive approach to tackling complex challenges.
  • Strong communication skills, with the ability to convey technical concepts to non-technical
  • stakeholders.
  • Strong analytical, strategic, and creative problem-solving skills
  • Experience with data visualization tools (e.g., Tableau, matplotlib, ggplot) to present insights
  • effectively.
  • Knowledge of SQL and databases.
  • Proficiency in programming languages such as Python, R, or Java, and experience with data manipulation libraries (e.g., Pandas, NumPy).
  • Hands-on experience with machine learning libraries and frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
  • A team player with the ability to collaborate effectively with cross-functional teams.
  • Strong interest in emerging technology, software, and IoT.
  • Strong interest in working in remote fast-paced environments on distributed teams to help shape and drive scalable growth in AI/ML.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Category: Data Science Jobs

Tags: AWS Azure Computer Science Data analysis Data visualization EDA GCP Java Machine Learning Mathematics Matplotlib ML models NumPy Pandas Python PyTorch R Scikit-learn Security SQL Statistics Tableau TensorFlow Testing

Perks/benefits: Career development

Region: North America
Country: United States

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