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Associate Data Scientist Deep Learning Jobs in Colorado

Cymertek Corporation

Data Scientist

Aurora, CO · On-site

Cymertek Corporation is seeking a curious and innovative Data Scientist to join their team and help ... of deep learning frameworks • Familiarity with cloud platforms • Experience with A/B testing ...

Cymertek Corporation

Data Scientist

Aurora, CO · On-site

... deep learning techniques • Expertise in natural language processing (NLP) • Understanding of database management systems • Experience in deploying models to production • Strong problem ...

ICR, Inc.

Data Scientist - Aurora, CO

Aurora, CO · On-site

$78K - $236K/yr

Data Scientist Aurora, CO Applications will be accepted on an ongoing basis. ICR has opportunities ... Experience with Deep Learning technologies such as Caffe, Theano, TensorFlow, or Neon. * Bayesian ...

Cymertek

Data Scientist

Aurora, CO · On-site

Data Scientist LOCATION Aurora, CO 80014 CLEARANCE TS/SCI Full Poly (Please note this position ... Knowledge of deep learning frameworks * Familiarity with cloud platforms * Experience with A/B ...

ZR Sandbox

Data Scientist

Boulder, CO · On-site

$130K - $160K/yr

DEEP DIVE INTO THIS ROLE As a Data Scientist, you'll analyze large datasets, develop predictive ... Expertise in Python, SQL, and machine learning frameworks. * Strong analytical and communication ...

Cymertek

Data Scientist

Aurora, CO · On-site

Data Scientist LOCATION Aurora, CO 80014 CLEARANCE TS/SCI Full Poly (Please note this position ... Knowledge of deep learning techniques * Expertise in natural language processing (NLP)

Toyon

Deep Learning Algorithm Developer

Fort Collins, CO · On-site

$100K - $190K/yr

Our researchers apply AI/ML techniques to develop data processing automation and control solutions ... science, physics, and/or mathematics. Experience with PyTorch, TensorFlow, or other deep learning ...

Apogee Engineering, LLC

Data Scientist

Colorado Springs, CO · On-site

$155K - $190K/yr

... Learning, predictive modeling, statistical analysis, and hypothesis testing. * Maintain awareness ... Data Science Council of America (DASCA) certifications, such as Associate Big Data Engineer (ABDE ...

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All JobsAssociate Data Scientist Deep Learning JobsAssociate Data Scientist Deep Learning Jobs in Colorado

Associate Data Scientist Deep Learning information

What is the difference between Associate Data Scientist Deep Learning vs Data Scientist?

AspectAssociate Data Scientist Deep LearningData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related; familiarity with deep learning frameworksBachelor's or Master's in CS, Statistics, or related; broader data analysis skills
Work EnvironmentFocus on developing deep learning models, often in AI or ML teamsBroader data analysis, visualization, and modeling across various projects
Employer & Industry UsageTech companies, AI startups, research institutionsFinance, healthcare, retail, tech, and more

The main difference is that Associate Data Scientist Deep Learning specializes in developing deep learning models, requiring specific knowledge of neural networks and frameworks. Data Scientists have a broader scope, including traditional data analysis, statistical modeling, and visualization. Both roles often require similar educational backgrounds but differ in technical focus and project types.

What are the most commonly searched types of Data Scientist Deep Learning jobs in Colorado? The most popular types of Data Scientist Deep Learning jobs in Colorado are:
Associate Data Scientist Deep Learning jobs near you
Senior Data Scientist

Senior Data Scientist

R2 Technologies Corporation

Denver, CO • On-site

Full-time

Re-posted 3 days ago

Job description

Overview:
Job Title: Senior Data Scientist - Knowledge Domain: Product (Job ID: 2099)
Location: Work From Home - USA, Denver, Colorado 80237 - look for locals
Duration: July 15, 2025 - February 27, 2026
Company: Western Union
Hire Type: Contractor (Contract Only)
Standard Hours per Week: 40
JOB DESCRIPTION
Senior Data Scientist - Knowledge Domain: Product
We are seeking a technically advanced and product-oriented Senior Data Scientist to lead the development of machine learning and deep learning solutions that power intelligent decision-making and innovative products. This role is ideal for someone with extensive experience in building, evaluating, and deploying ML and neural network models in production environments. You'll collaborate cross-functionally to create and scale real-world AI applications that have direct impact on users and business performance.
Role Responsibilities:
Design, build, and evaluate machine learning and deep learning models for classification, regression, recommendation, NLP, computer vision, and time-series forecasting.
Apply deep learning techniques (e.g., CNNs, RNNs, LSTMs, Transformers) to solve complex, data-intensive problems.
Lead the development of ML products, from model prototyping through production deployment, performance monitoring, and continuous improvement.
Select appropriate architectures and hyperparameters, optimize model performance, and use proper evaluation metrics (e.g., AUC, F1, BLEU, IoU, perplexity) based on the use case.
Collaborate with product managers and engineers to translate business challenges into deployable solutions using AI/ML.
Design automated pipelines for data preprocessing, feature engineering, training, and inference (batch or real-time).
Evaluate model drift, monitor performance post-deployment, and implement retraining pipelines as part of a production MLOps system.
Mentor junior data scientists, contribute to code reviews, and lead technical discussions across the data science and engineering teams.
Role Requirements:
Bachelor's degree in Computer Science, Statistics, Applied Math, or related field (Master's or PhD strongly preferred).
5+ years of industry experience in applied machine learning, with 2+ years focused on deep learning and neural network applications.
Experience in Banking, Payments or Financial Services formulating AI data solutions that allow us to leverage our data to know our customers better and target our resources for better market penetration and focused attention and education.
Proficiency in Python and ML libraries such as scikit-learn, XGBoost, TensorFlow, Keras, or PyTorch.
Deep understanding of neural networks, model regularization, overfitting/underfitting prevention, and GPU-accelerated training.
Experience with customer data enrichments.
Proven track record of building, evaluating, and deploying machine learning models at scale in production environments.
Experience with cloud platforms (AWS/GCP/Azure), containerization, and model serving technologies.
Excellent communication skills, with the ability to present complex findings to both technical and non-technical stakeholders.
Hands-on experience with real-world applications of deep learning, such as recommendation engines, fraud detection, customer segmentation, document summarization, image recognition, or speech processing.
Familiarity with MLOps tools (e.g., MLflow, SageMaker, Airflow, Kubeflow).
Experience with CI/CD for ML, feature stores, and real-time inference systems.
Contributions to academic research, open-source ML projects, or ML/AI patents.
Skills:
Knowledge Domain

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