

Senior Data Scientist (W2 Only - Open for Visa Sponsorship)
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Scientist, 12+ months, paying "pay rate". Located in Findlay, OH or San Antonio, TX (4 days on-site, 1 day remote). Requires expertise in AI/ML, Python, TensorFlow, and deep learning, with 5+ years of experience.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
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ποΈ - Date discovered
June 11, 2025
π - Project duration
More than 6 months
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ποΈ - Location type
Remote
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π - Contract type
W2 Contractor
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π - Security clearance
Unknown
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π - Location detailed
San Antonio, Texas Metropolitan Area
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π§ - Skills detailed
#Scala #Strategy #Deep Learning #"ETL (Extract #Transform #Load)" #AI (Artificial Intelligence) #Neural Networks #Forecasting #AWS (Amazon Web Services) #Python #Visualization #Cloud #Keras #Deployment #ML (Machine Learning) #Data Architecture #NLP (Natural Language Processing) #Computer Science #Data Analysis #Data Engineering #Transformers #Mathematics #PyTorch #Storage #Data Science #TensorFlow #Statistics #Big Data #Datasets #Databases #Azure #Model Optimization
Role description
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Position: Senior Data Scientist
Location: Findlay OH, or San Antonio TX (4 days on-site/1 day remote per week)
Duration: 12+ months
Job Description
We are seeking a highly skilled and experienced Senior Data Scientist with a specialization in AI/ML Engineering to join our dynamic Data Science and AI team. In this role, you will be instrumental in transforming data into actionable insights and innovative solutions that drive our business strategy forward. You will leverage advanced machine learning, deep learning, and neural network techniques to solve complex business challenges, collaborating closely with cross-functional teams to design, develop, and deploy scalable AI-driven models and algorithms. This position offers the opportunity to be at the forefront of AI/ML advancements.
Key Responsibilities
β’ Solution Development: Engage in the ideation, prototyping, and implementation of new AI/ML solutions to meet emerging business requirements.
β’ Machine Learning Pipelines: Design, develop, and implement end-to-end machine learning pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment.
β’ Deep Learning Models: Develop, train, and optimize deep learning models using neural network architectures (e.g., CNNs, RNNs, Transformers, GANs) and frameworks such as TensorFlow, Keras, or PyTorch. Apply these models to solve complex problems in areas like computer vision, natural language processing (NLP), and time-series forecasting.
β’ Collaboration: Work closely with data architects, data engineers, and software developers to ensure effective data collection, processing, and storage. Collaborate with external partners, research institutions, and subject matter experts to gather domain-specific knowledge and datasets.
β’ Exploratory Data Analysis: Perform exploratory data analysis to identify patterns, generate insights, and communicate findings to stakeholders.
β’ Model Optimization: Optimize model performance by addressing issues such as overfitting, underfitting, and bias, ensuring scalability and performance in production environments.
β’ Mentorship: Mentor junior data scientists in model development, data handling, and ethical considerations in AI/ML practices.
β’ Continuous Learning: Stay abreast of the latest advancements in machine learning and AI research, applying new methods to enhance model performance and scalability.
Desired Skills and Experience
β’ Education: Masterβs or Ph.D. in Computer Science, Statistics, Mathematics, or a related field with 5+ years of relevant experience.
β’ Technical Proficiency: Expertise in Python and proficiency in machine learning frameworks (TensorFlow, PyTorch, scikit-learn). Experience with cloud platforms such as Azure, AWS, or Google Cloud for deploying big data and ML solutions.
β’ Deep Learning Expertise: Extensive hands-on experience in applying deep learning techniques and neural networks to real-world problems, particularly in industrial analytics. Proven ability to develop, train, and optimize models for high-impact applications such as image recognition, NLP, and multimodal modeling.
β’ Analytical Skills: Strong problem-solving, critical thinking, and analytical capabilities. Experience with both relational and non-relational databases, time-series data, and data visualization techniques.
β’ Communication: Excellent verbal and written communication skills with the ability to convey complex technical concepts to non-technical stakeholders clearly and effectively.
β’ Collaboration: A strong team player mindset capable of working collaboratively within diverse teams and contributing to an inclusive work environment.
β’ Continuous Learning: A pronounced passion for continuous learning and staying ahead in AI/ML fields, with enthusiasm for applying new technologies to solve real-world problems.