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Senior Data Analyst Machine Learning Jobs in Oklahoma

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As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

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As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

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Senior Data Analyst Machine Learning information

What is the difference between Senior Data Analyst Machine Learning vs Data Scientist?

AspectSenior Data Analyst Machine LearningData Scientist
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; experience with machine learning toolsBachelor's or Master's in Data Science, Computer Science, or related; strong programming and statistical skills
Work EnvironmentData analysis teams, business units, focus on applying ML models to business problemsResearch and development teams, focus on model development, experimentation, and innovation
Employer & Industry UsageFinance, healthcare, retail, and tech companies using ML for insightsTech firms, startups, research institutions developing advanced models

While both roles involve working with data and machine learning, Senior Data Analyst Machine Learning typically focuses on applying existing models to solve business problems, whereas Data Scientists develop new models and algorithms, often engaging in more research and experimentation.

How does a Senior Data Analyst specializing in Machine Learning typically collaborate with data science and engineering teams?

As a Senior Data Analyst with a focus on Machine Learning, you'll work closely with both data science and engineering teams to bridge the gap between data insights and model deployment. You may be responsible for preparing and analyzing large datasets, communicating findings and business needs to data scientists, and ensuring that machine learning models are implemented effectively. Regular collaboration includes participating in code reviews, refining feature engineering, and translating technical results into actionable business recommendations. This cross-functional teamwork is key to ensuring that projects move smoothly from conception to production.

What are the key skills and qualifications needed to thrive as a Senior Data Analyst Machine Learning, and why are they important?

To thrive as a Senior Data Analyst Machine Learning, you need strong analytical skills, expertise in statistics, and advanced proficiency in programming languages like Python or R, typically supported by a degree in a quantitative field. Familiarity with machine learning frameworks (such as scikit-learn, TensorFlow, or PyTorch), data visualization tools, and experience with SQL databases are essential, along with relevant certifications like Google Data Analytics or AWS Machine Learning. Outstanding problem-solving abilities, collaboration, and the capacity to communicate complex concepts clearly make individuals stand out in this role. These skills and qualities are crucial for extracting actionable insights from data, building effective predictive models, and driving data-driven decision-making within organizations.

What is a Senior Data Analyst in Machine Learning?

A Senior Data Analyst in Machine Learning is a professional who analyzes large datasets to extract insights and supports the development and implementation of machine learning models. They often work closely with data scientists, engineers, and business stakeholders to identify trends, prepare data, and ensure the quality and relevance of data used in machine learning projects. Their role typically includes advanced data analysis, developing data pipelines, creating reports, and interpreting the results of machine learning models to drive business decisions.
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Senior Data Analyst Machine Learning jobs near you
Infographic showing various Senior Data Analyst Machine Learning job openings in Oklahoma as of July 2026, with employment types broken down into 69% Full Time, 6% Part Time, and 25% Contract. Highlights an 61% Physical, 5% Hybrid, and 34% Remote job distribution.

Data Analyst III/II/I

Americanfidelity

Oklahoma City, OK

Full-time

Re-posted 12 days ago

Job description

* Plan, implement and execute data mining and predictive modeling related projects to which they are assigned to deliver intended business value propositions, on time and within scope according to agreed upon priorities. The Data Analyst is accountable for working collaboratively with Data Navigators and for the successful delivery of all projects under their supervision.

* Assist the Research & Development team, Executive Management, and AFA through the production and maintenance of data and metrics regarding demographics, market trends, behavioral economics, and socioeconomic shifts.

* Drive business value through actionable insight and opportunity identification as facilitated through comprehensive exploratory, interactive, adaptive, and iterative data mining, machine learning, data science, clustering, artificial intelligence (AI), and predictive modeling related analysis which have generally high complexity and/or business risk.

Skills of Ideal Candidate:

1. Advanced knowledge of one or more differing statistical programming languages such as SAS, R or Stata.

2. Ability to develop structure and/or program databases specifically within an MS SQL environment, skilled in the utilization of Structured Query Language (SQL) for interacting with data sets. Understanding of data structures and ability to become proficient in mining data structures and lineage in support of data foot printing and inventory techniques.

3. Skilled in Robotic Process Automation tools such as UI Path and Artificial Intelligence tools like Data Robot

4. Skilled in MS Office Suite including MS Access, Excel, PowerPoint, Word and MS SharePoint.

5. Familiarity with the following disciplines

Natural Language Processing: Interaction between computers and humans

Machine Learning: using computers to improve as well as develop algorithms

Conceptual modeling: to be able to share and articulate conceptual approaches to solving business questions/problems

Statistical analysis and Predictive modeling

Hypothesis testing: design hypothesis, document control and test with appropriate modeling and experimentation

6. Ability to query databases and datasets and perform statistical analysis on enterprise-class database systems.

7. Exceptional presentation skills.

8. Being able to work in a fast-paced multidisciplinary environment as in a competitive landscape new data keeps flowing in rapidly and the world is constantly changing.

9. Strong negotiation skills.

10.Strong communication skills, including written, verbal and listening which can be deployed successfully when addressing entry level Colleagues to management to senior executives. This includes the ability to speak confidently in both business and technological surroundings and appropriately transliterate between the two.

11. Exceptional analytical thinking and problem solving skills.

12. Exceptional understanding of business and business strategy.

13.Strongplanning skills.

14. Exceptional organizational skill and ability to work autonomously.

15. Experience using data visualization tools such as QlikSense or Tableau

16. Innovative curiosity

17.Strongknowledge of Data Science

18.Ability to deal with ambiguity

Education Requirements:

Data Analyst III: Actuarial Designationscan substitute for PhD.AFA specific data experience will be considered in lieu of PhD oncase by casebasis

Data Analyst I/II: High school diploma or equivalent

#AFC

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