Data Scientist: III (Senior)
Columbus, OH · On-site +1
Strong experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker) * Strong ... Remote roles will also have the opportunity to come together in our offices for moments that matter.
Data Scientist: III (Senior)
Columbus, OH · On-site +1
Strong experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker) * Strong ... Remote roles will also have the opportunity to come together in our offices for moments that matter.
Data Scientist: III (Senior)
Columbus, OH · On-site +1
Strong experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker) * Strong ... Remote roles will also have the opportunity to come together in our offices for moments that matter.
Data Scientist: III (Senior)
Columbus, OH · On-site +1
Strong experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker) * Strong ... Remote roles will also have the opportunity to come together in our offices for moments that matter.
Data Scientist: III (Senior)
Columbus, OH · On-site +1
... technologies (e.g., AWS Sagemaker) Strong experience with machine learning environments (e.g ... Remote roles will also have the opportunity to come together in our offices for moments that matter.
Data Scientist: III (Senior)
Columbus, OH · On-site +1
... technologies (e.g., AWS Sagemaker) Strong experience with machine learning environments (e.g ... Remote roles will also have the opportunity to come together in our offices for moments that matter.
Lead AI Engineer - AWS Platform
Columbus, OH · On-site +1
$130K - $190K/yr
Medical
Dental
Vision
Life
Retirement
PTO
Amazon SageMaker, AWS Lambda, S3, Glue, EKS, and related services * Contribute to evolving use of ... Flexible work schedules and hybrid/remote options for eligible positions * Educational assistance ...
Lead AI Engineer - AWS Platform
Columbus, OH · On-site +1
$130K - $190K/yr
Medical
Dental
Vision
Life
Retirement
PTO
Amazon SageMaker, AWS Lambda, S3, Glue, EKS, and related services * Contribute to evolving use of ... Flexible work schedules and hybrid/remote options for eligible positions * Educational assistance ...
Aws Sagemaker Remote information
What is an AWS SageMaker remote job?
An AWS SageMaker remote job typically refers to a position where professionals use Amazon SageMaker, a cloud-based machine learning platform, to develop, train, and deploy machine learning models while working remotely. These roles often involve collaborating with teams via online tools, performing data analysis, and building models using SageMaker's suite of features without having to be physically present in an office. This allows for flexibility and access to global talent, as all work can be conducted over the internet while leveraging AWS infrastructure.
What are the key skills and qualifications needed to thrive as an AWS SageMaker remote specialist?
To thrive as an AWS SageMaker Remote Specialist, you need expertise in machine learning, data science, cloud computing, and a strong understanding of AWS services, often supported by a degree in computer science or a related field. Familiarity with tools like Jupyter Notebooks, Python, TensorFlow, and official AWS certifications such as AWS Certified Machine Learning – Specialty are typically required. Excellent problem-solving, teamwork, and communication skills help you collaborate with distributed teams and translate business needs into technical solutions. These competencies are crucial for efficiently building, deploying, and managing scalable machine learning models in a remote cloud environment.
What are some common challenges faced by AWS SageMaker professionals working remotely, and how can they be addressed?
Remote AWS SageMaker professionals often encounter challenges such as managing secure access to sensitive data, collaborating effectively with distributed teams, and ensuring consistent deployment environments. To address these, it's important to leverage AWS security best practices, use version control and documentation tools, and participate in regular virtual meetings to stay aligned with team members. Additionally, taking advantage of AWS’s integrated collaboration features and establishing clear communication protocols can help mitigate these obstacles and ensure project success.
What is the difference between Aws Sagemaker Remote vs Data Scientist?
| Aspect | Aws Sagemaker Remote | Data Scientist |
|---|---|---|
| Required Credentials | AWS certifications, cloud computing skills | Statistics, data analysis, programming (Python/R) |
| Work Environment | Cloud platforms, remote or on-premise | Office, remote, or hybrid |
| Industry Usage | Machine learning deployment, cloud services | Data analysis, modeling, research |
While Aws Sagemaker Remote focuses on deploying and managing machine learning models on AWS cloud, Data Scientists primarily analyze data, build models, and generate insights. Both roles require technical skills, but Sagemaker Remote emphasizes cloud infrastructure and deployment, whereas Data Scientists focus on data analysis and modeling.
What are popular job titles related to Aws Sagemaker Remote jobs in Ohio?
For Aws Sagemaker Remote jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Aws Sagemaker Remote jobs in Ohio look for?
The top searched job categories for Aws Sagemaker Remote jobs in Ohio are:
What cities in Ohio are hiring for Aws Sagemaker Remote jobs?
Cities in Ohio with the most Aws Sagemaker Remote job openings:
Full-time
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Job description
Description
Summary:
The Senior Data Scientist contributes to building and developing the organization’s data infrastructure and supports the senior leadership with insights, management reports, and analysis for decision-making processes.
Duties and Responsibilities:
- Performs advanced analytics methods to extract value from business data.
- Performs large-scale experimentation and build data-driven models to answer business questions.
- Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence.
- Determines requirements that will be used to train and evolve deep learning models and algorithms.
- Articulates a vision and roadmap for the exploitation of data as a valued corporate asset.
- Influences product teams through presentation of data-based recommendations.
- Evangelizes best practices to analytics and products teams.
- Owns the entire model development process, from identifying the business requirements, data sourcing, model fitting, presenting results, and production scoring.
- Performs other duties as assigned.
Basic Qualifications:
- Master’s Degree in computer science, statistics, economics or related fields
- 3+ years of work and/or educational experience in machine learning or cloud computing, experience using statistics and machine learning to solve complex business problems, experience conducting statistical analysis with advanced statistical software, experience scripting languages, and packages, experience building and deploying predictive models, experience web scraping, and scalable data pipelines and experience with big data analysis tools and techniques.
Preferred Qualifications:
- Up-to-date knowledge of machine learning and data analytics tools and techniques
- Strong knowledge in predictive modeling methodology
- Experienced at leveraging both structured and unstructured data sources
- Willingness and ability to learn new technologies on the job
- Demonstrated ability to communicate complex results to technical and non-technical audiences
- Demonstrated ability to work effectively in teams as well as independently across multiple tasks while meeting aggressive timelines
- Strategic, intellectually curious thinker with focus on outcomes
- Professional image with the ability to form relationships across functions
- Strong experience with R/RStudio, Python, SAS, SQL, NoSQL
- Strong experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker)
- Strong experience with machine learning environments (e.g., TensorFlow, scikit-learn, caret)
- Strong understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling
- Financial Services background
Exempt Status: (Yes = not eligible for overtime pay) (No = eligible for overtime pay)
Workplace Type:
OfficeOur Approach to Office Workplace Type
Certain positions outside our branch network may be eligible for a flexible work arrangement. We’re combining the best of both worlds: in-office and work from home. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. Remote roles will also have the opportunity to come together in our offices for moments that matter. Specific work arrangements will be provided by the hiring team.
Huntington is an Equal Opportunity Employer.
Tobacco-Free Hiring Practice: Visit Huntington's Career Web Site for more details.
Note to Agency Recruiters: Huntington Bank will not pay a fee for any placement resulting from the receipt of an unsolicited resume. All unsolicited resumes sent to any Huntington Bank colleagues, directly or indirectly, will be considered Huntington Bank property. Recruiting agencies must have a valid, written and fully executed Master Service Agreement and Statement of Work for consideration.