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Internship Applied Scientist Machine Learning Jobs in Ohio

As a Data Scientist Lead - WFP Machine Learning Scientist, within JPMorganChase, you will engage in projects by the Artificial Intelligence(AI)/Machine Learning(ML) team that can be complex, data ...

On the Global Specialty Applied AI team, we utilize the latest AI products and frameworks to ... Adopt and promote MLOps best practices to the Data Science community. Minimum Requirements Must be ...

Data Scientist

Cincinnati, OH · On-site

$85K - $122K/yr

... Applied Mathematics, Statistics, Physics, Analytics, etc.) or possess equivalent work experience ... Proficient in programming languages such as Python and familiar with data science/machine learning ...

On the Global Specialty Applied AI team, we utilize the latest AI products and frameworks to ... Adopt and promote MLOps best practices to the Data Science community. Minimum Requirements * Must ...

The Applied AI Scientist III is responsible for the development and application of cutting-edge ... Utilize machine learning algorithms to identify patterns, trends, and opportunities for improving ...

Required : • Proven experience with Python or C#, SQL, and applied machine learning or ... Science, or Computer Science (or equivalent experience in industry). • Math optimization and ...

Senior Machine Learning Engineer

Columbus, OH · On-site +1

$100K - $138K/yr

This role sits at the intersection of generative modeling, robotics, and applied physics. It is ... Master's or PhD in Computer Science, Robotics, Machine Learning, or related field, or equivalent ...

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Internship Applied Scientist Machine Learning information

What types of projects do Internship Applied Scientists in Machine Learning typically work on, and how do they contribute to the team's goals?

Internship Applied Scientists in Machine Learning often collaborate with multidisciplinary teams to tackle real-world problems using data-driven approaches. Typical projects might include developing and fine-tuning machine learning models, conducting experiments to validate hypotheses, or assisting in the deployment of algorithms into production systems. Interns are expected to contribute fresh perspectives, help with data preprocessing, and perform thorough model evaluations. Through these projects, interns gain hands-on experience while directly supporting the team's research and product development objectives.

What is the difference between Internship Applied Scientist Machine Learning vs Internship Data Scientist?

AspectInternship Applied Scientist Machine LearningInternship Data Scientist
Required CredentialsRelevant degrees in Computer Science, Data Science, or related fields; knowledge of ML frameworksDegrees in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentResearch and development teams, focus on ML model developmentBusiness teams, focus on data analysis and insights
Employer & Industry UsageTech companies, AI-focused organizationsVarious industries including tech, finance, healthcare
Comparison Search IntentUnderstanding roles in ML research and developmentUnderstanding data analysis and business insights roles

Internship Applied Scientist Machine Learning roles focus on developing and applying machine learning models, often in research settings. In contrast, Internship Data Scientist positions emphasize analyzing data to generate insights for business decisions. Both roles require strong analytical skills and relevant educational backgrounds, but they differ in their primary focus and work environment.

What are the key skills and qualifications needed to thrive as an Internship Applied Scientist in Machine Learning, and why are they important?

To thrive as an Internship Applied Scientist in Machine Learning, you need a solid background in mathematics, statistics, and computer science, often supported by coursework or research experience in machine learning and data analysis. Familiarity with tools such as Python, TensorFlow, PyTorch, and experience working with large datasets are highly valued, along with knowledge of version control systems like Git. Strong problem-solving skills, curiosity, and the ability to communicate complex concepts clearly set top candidates apart. These competencies are crucial for effectively designing, implementing, and presenting machine learning solutions that address real-world challenges.

What does an Internship Applied Scientist in Machine Learning do?

An Internship Applied Scientist in Machine Learning works on real-world projects involving the design, development, and evaluation of machine learning models and algorithms. Their responsibilities typically include data analysis, building predictive models, experimenting with new techniques, and collaborating with engineers and researchers to solve complex problems. Interns gain hands-on experience with tools like Python, TensorFlow, or PyTorch, and contribute to advancing the company's AI capabilities. The role requires a strong foundation in mathematics, statistics, and computer science, as well as the ability to communicate findings to both technical and non-technical stakeholders.
What are the most commonly searched types of Applied Scientist Machine Learning jobs in Ohio? The most popular types of Applied Scientist Machine Learning jobs in Ohio are:
What are popular job titles related to Internship Applied Scientist Machine Learning jobs in Ohio? For Internship Applied Scientist Machine Learning jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Internship Applied Scientist Machine Learning jobs in Ohio look for? The top searched job categories for Internship Applied Scientist Machine Learning jobs in Ohio are:
WFP Machine Learning Scientist

WFP Machine Learning Scientist

J.P. Morgan

Columbus, OH • On-site, Remote

Full-time

Medical, Retirement

Posted 22 days ago


Job description

hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role.

JOB DESCRIPTION

The Workforce Planning (WFP) organization is a part of Consumer and Community (CCB) Operations division. The WFP Data Science organization is tasked with delivering quantitatively driven solutions to support the core WFP functions (demand forecasting, capacity planning, resource scheduling, and business analysis & support). The WFP organization supports Chase’s call centers, back office, and ~5,200 retail branches.

As a Data Scientist Lead - WFP Machine Learning Scientist, within JPMorganChase, you will engage in projects by the Artificial Intelligence(AI)/Machine Learning(ML) team that can be complex, data intensive, and of a high level of difficulty, each having significant impact on the business.  You will typically encounter these problems which will be of an unstructured nature, whereby the employee will be expected to quickly assess and comprehend the situation then develop a practical problem solving strategy.  You will be expected to analyze the topic in question, develop solution proposals and review their results and next steps with management for prioritization, timing, and delivery. The AI/ML team is tasked with building next-gen data science solutions that move us closer to real-time inference and decision making.

Job Responsibilities

  • Design and development of Machine Learning, Artificial Intelligence and Statistical models.
  • Participate in the full model development lifecycle, from framing the problem to prepare documentation and passing independent model review (MRGR).
  • Lead AI/ML projects along with mentor and coach junior team members.
  • Collaborate with stakeholders to understand the business requirements and clearly define the objectives of any solution.
  • Identify and select the correct method to solve the problem while staying up to data on the latest AI/ML research
  • Ensure the robustness of any data science solution.
  • Develop and communicate recommendations and data science solutions in easy-to-understand-way leveraging data to tell a story.
  • Lead and persuade others while positively influencing the outcome of team efforts and help frame a business problem into a technical problem resulting in a feasible solution.

Required Qualifications, Capabilities, and Skills

  • Master’s Degree with 5+ years or Doctorate (PhD) with 3+ years of experience operating as an data science professional (e.g. data scientist, statistician, or related professions) in a quantitative field: Statistics, Analytics, Data Science, Engineering, Operations Research, Economics, Mathematics, Machine Learning, Artificial Intelligence, and related disciplines.
  • 2+ years of experience leading AI/ML projects with multiple team members
  • Hands-on experience developing statistical models, machine learning models, and/or artificial intelligence models.
  • Deep understanding of math and theory behind AI/ML algorithms.
  • Proficient in data science programming languages like Python, R or Scala.
  • Experience with big-data technologies such as Hadoop, Spark, SparkML, etc. & familiarity with basic data table operations (SQL, Hive, etc.).
  • Demonstrated relationship building skills, with a superior ability to make things happen through the use of positive influence. 

Preferred Qualifications, Capabilities, and Skills

  • Advanced expertise with Time Series and Operations Research techniques. 
  • Natural Language Processing(NLP)/Natural Language Generation(NLG), Neural Nets, or other ML/AI skills.
  • Prior experience with public cloud technologies such as Amazon Web Services(AWS), Azure or Google Cloud Platform(GCP).
  • Previous experience leading highly complex cross-functional technical projects with multiple stakeholders

This position is full time in office Monday - Friday.  This position is not hybrid nor remote.

ABOUT US

Chase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.  We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

ABOUT THE TEAM
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.
The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.