Pitchbook

Deep Learning Data Scientist II

Pitchbook • $110K — $130K *
Dallas, TX 75217In-Person
Healthcare
Less than 5 years of experience
Today
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Job Overview by Ladders

Qualifications

  • M.S. or Ph.D. in a related quantitative field.
  • 2+ years of relevant experience in computer vision after obtaining degree.
  • Strong programming skills in Python with experience in machine learning applications.
  • Familiarity with state-of-the-art deep learning models (e.g., vision transformers).
  • Proficient in deep learning frameworks like PyTorch and TensorFlow.

Responsibilities

  • Research and develop AI/ML algorithms for computer vision in healthcare.
  • Implement efficient model deployment pipelines for scalable inference.
  • Optimize models for performance while ensuring accuracy.
  • Maintain high data quality throughout the project lifecycle.
  • Collaborate with clinical partners to translate needs into AI/ML solutions.
  • Independently manage R&D projects from inception to delivery.
  • Document and share knowledge using version-controlled workflows.

Benefits

  • Opportunity to work at the intersection of AI and healthcare.
  • Access to cutting-edge technologies and methodologies in deep learning.
  • Chance to collaborate with cross-functional teams and clinical experts.
Full Job Description
Position Summary:

We are seeking a motivated Data Scientist to research, develop, and enhance AI/ML algorithms for computer vision and healthcare applications. This role involves developing and improving deep learning models, maintaining high standards of data quality, optimizing models for efficient deployment, and translating advances in AI research into practical healthcare solutions. The Data Scientist will collaborate with clinical partners and internal stakeholders to understand clinical and business needs and develop appropriate technical solutions. The ideal candidate will be capable of independently managing research and development projects while contributing effectively within cross-functional teams. Success in this role requires strong technical and communication skills, attention to detail, persistence, and a commitment to staying current with advances in AI/ML and computer vision.

Essential Duties and Responsibilities:

  • Research, develop, evaluate, and enhance machine learning and deep learning algorithms for computer vision applications, translating advances in AI research into practical healthcare solutions.
  • Implement and optimize model deployment pipelines to enable efficient, scalable, and hardware-optimized inference.
  • Apply model optimization techniques to improve computational efficiency and inference performance while maintaining model accuracy.
  • Maintain data quality and integrity throughout the data lifecycle to support robust algorithm development, training, and evaluation.
  • Collaborate with clinical partners and internal stakeholders to understand clinical and business needs and translate them into appropriate AI/ML solutions.
  • Independently manage assigned research and development projects from problem formulation through implementation, evaluation, and delivery.
  • Ensure reproducibility of analyses and experiments through clear documentation, version-controlled workflows, and effective knowledge sharing.
  • Stay current with advances in AI/ML, computer vision, and related technologies and evaluate their applicability to ongoing research and development.
  • Communicate technical methods, results, and recommendations effectively to both technical and non-technical stakeholders.


Qualifications:

  • M.S. or Ph.D. in Computer Science, Electrical Engineering, Biomedical Engineering, Statistics, Applied Mathematics, or a related quantitative field.
  • Minimum of two years of relevant research or professional experience in computer vision. For candidates with a master's degree, the required experience must be professional experience obtained after completion of the degree.


Knowledge, Skills, and Abilities:

  • Strong programming skills in Python and experience developing maintainable, reproducible code for machine learning applications.
  • Strong foundation in state-of-the-art deep learning architectures (e.g., vision transformers) for computer vision tasks including image classification, object detection, and semantic segmentation.
  • Proficiency with deep learning frameworks and libraries, including PyTorch and TensorFlow.
  • Strong understanding of AI/ML evaluation metrics, benchmarking methodologies, and best practices for rigorous computer vision model validation.
  • Solid understanding of model optimization techniques, including pruning, quantization, mixed-precision inference, and other strategies for improving computational efficiency and inference performance.
  • Working knowledge of model deployment and inference tools, such as ONNX, LibTorch, and TensorRT.
  • Self-driven and capable of independently navigating ambiguous research problems, working with incomplete data, and delivering high-quality results.
  • Strong written and verbal communication skills, including the ability to prepare technical documentation, reports, and scientific manuscripts.


Preferred Qualifications:

  • Experience working with multispectral and/or hyperspectral imaging data.
  • Experience with generative AI models for medical image synthesis and simulation.
  • Experience applying AI/ML methodologies to healthcare or biomedical applications, with demonstrated contributions to successful research, clinical, or product outcomes.


Physical Requirements:

Prolonged periods of sitting at a desk and working on a computer.

Travel:

N/A

About Pitchbook

PitchBook is a financial data and software company that provides research, analysis, and data on private equity, venture capital, and M&A transactions. The company's platform offers a range of tools and services, including market research, deal sourcing, due diligence, and portfolio management. PitchBook serves a variety of clients, including investment banks, private equity firms, venture capital firms, and corporate development teams. The company was founded in 2007 and is headquartered in Seattle, Washington.
Learn more about Pitchbook
Size
1,000 employees
Industry
Finance & Insurance
Founded
2007
* Ladders Estimates

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