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Weekend Data Scientist Deep Learning Jobs (NOW HIRING)

In this role, you will be responsible for designing, developing, and implementing innovative Deep Learning models, driving innovation, and providing technical leadership to a team of data scientists.

Data Scientist Position Summary: We are seeking a highly skilled and motivated Data Scientist to ... Deep Learning Frameworks * Demonstrate expertise in deep learning frameworks such as TensorFlow and ...

Conversica is seeking talented and passionate data scientists to help us evolve our artificial ... Training in deep learning approaches and natural language processing * Advanced proficiency with ...

Role: Data Scientist Location: Irving, TX - Fulltime Position Data Scientist with Generative AI ... Machine learning, NLP & deep learning: Strong understanding of supervised and unsupervised learning ...

Build NLP pipelines using deep learning frameworks such as PyTorch , TensorFlow , or similar ... Core Data Science Engineering & MLOps * Work in Databricks for ETL, feature engineering, ML ...

Data Scientist

Clayton, MO · On-site

$49 - $70/hr

Do you have experience designing and deploying deep learning models using tools like TensorFlow or ... You will work within the data science team to develop and deploy advanced models that support ...

Data Scientist

New York, NY · On-site

$173K - $175K/yr

Design, train, and implement ML/deep learning architectures. * Establish evaluation metrics ... Data Scientist or a related occupation. Must have at least three (3) years of experience with the ...

Strong Time Series forecasting, ML, deep learning and standard statistical methods to evaluate models. Experience working on supply chain projects. We are seeking a highly skilled Data Scientist to ...

Stay up-to-date on state-of-the-art research in data science, deep learning, and security-specific AI to drive platform innovation. * Explore novel statistical methods and machine learning techniques ...

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Weekend Data Scientist Deep Learning information

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$37.5K

$122.7K

$196.5K

How much do weekend data scientist deep learning jobs pay per year?

As of Sep 11, 2026, the average yearly pay for weekend data scientist deep learning in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is the difference between Weekend Data Scientist Deep Learning vs Weekend Data Analyst?

AspectWeekend Data Scientist Deep LearningWeekend Data Analyst
Required CredentialsTypically requires a degree in Data Science, Computer Science, or related fields; knowledge of deep learning frameworksUsually requires a degree in Data Analysis, Statistics, or related fields; proficiency in Excel, SQL, and basic analytics tools
Work EnvironmentOften involves working on complex machine learning models, coding in Python or R, and experimenting with neural networksFocuses on data cleaning, reporting, and visualization, often using Excel, Tableau, or Power BI
Employer & Industry UsageUsed in tech companies, research institutions, and AI-focused startupsCommon in finance, marketing, healthcare, and retail sectors

Weekend Data Scientist Deep Learning roles focus on developing advanced AI models and require programming skills, while Weekend Data Analysts handle data interpretation and reporting. Both roles are valuable but differ in technical complexity and industry application.

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What other helpful pages are available for Weekend Data Scientist Deep Learning?

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Infographic showing various Weekend Data Scientist Deep Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

ML Research Scientist -Deep Learning & Transformer Architectures

New York, NY • On-site

$150K - $200K/yr

Full-time

Re-posted 5 days ago


Millennium Management rating

7.0

Company rating: 7.0 out of 10

Based on 12 frontline employees who took The Breakroom Quiz


Job description

ML Research Scientist -Deep Learning & Transformer Architectures
Please direct all resume submissions to QuantTalentUS@mlp.com and reference REQ-29605 in the subject.
Overview
As part of a long-term research agenda within a newly formed systematic equities pod, we are building a proprietary Transformer-based model trained on tokenized intraday market data for next-token prediction of price movements.
We are seeking an exceptional ML research scientist with deep expertise in Transformer architectures and large-scale model training. You will design, implement, and train a custom decoder-only Transformer from scratch -not fine-tune an existing LLM, but build a purpose• built architecture for financial time-series.
This is a long-term research project with significant computational resources. The successful candidate will have a PhD in machine learning or a related field and demonstrated ability to implement Transformer architectures from first principles.
Principal Responsibilities
• Design and implement a custom decoder-only Transformer architecture optimized for tokenized financial time-series data
• Develop a novel tokenization scheme for intraday market data: price movements, volume, order flow, and cross-sectional features
• Implement efficient training pipelines using PyTorch with mixed-precision training, gradient checkpointing, and multi-GPU parallelism
• Design attention mechanisms adapted to financial data: temporal attention patterns, cross-asset attention, and multi-scale representations
• Build evaluation frameworks for next-token prediction accuracy, signal quality, and trading performance
• Implement inference optimization for low-latency production deployment: model quantization, KV-cache, speculative decoding
• Conduct rigorous ablation studies to validate architecture choices and training methodology
• Collaborate with the team to integrate model predictions into the live trading pipeline
• Document research methodology, experimental results, and architectural decisions
Required Skills / Qualifications
• PhD in Machine Learning, Computer Science, Statistics, Applied Mathematics, or a related field with a focus on deep learning
• Demonstrated ability to implement Transformer architectures from scratch (not just finetuning pre-trained models)
• Deep understanding of attention mechanisms, positional encodings, tokenization strategies, and training dynamics
• Expert-level PyTorch skills including custom modules, training loops, mixed-precision, and multi-GPU training
• Strong mathematical foundations: linear algebra, probability theory, optimization, information theory
• Experience training models at scale (100M+ parameters)
• Strong programming skills in Python and C++ for performance-critical components
• Self-directed researcher capable of defining and executing a multi-month research agenda
• Familiarity with Al-assisted development tools (Cursor, Claude Code)
Preferred Skills / Experience
• Experience applying deep learning to financial data or time-series forecasting
• Familiarity with tokenizatlon approaches for continuous or non-text data
• Published research in top ML venues (NeurlPS, ICML, ICLR) or equivalent industry experience
• Knowledge of market microstructure and intraday trading dynamics
• Experience with model compression, quantization, and inference optimization
Millennium offers a total compensation package which includes a base salary, discretionary performance bonus, and comprehensive benefits. The estimated base salary range for this position is $150,000 to $200,000, which is specific to New York and may change in the future. When finalizing an offer, we take into consideration an individual's experience level and the qualifications they bring to the role to formulate a competitive total compensation package.

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