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Mining Data Analytics Jobs in Oklahoma (NOW HIRING)

Utilize data mining and analytics/AI methods to generate key insights into prospects, such as gaps in services, excessive fees, benchmarks for improvements, elevated fiduciary exposure, financial ...

Data Scientist

Oklahoma City, OK · On-site

$70 - $90/hr

Work with multiple data platforms to perform ad hoc reporting, database mining, and analysis that provide a better understanding of the customer * Partner with Marketing and other business units to ...

Senior Workforce Analytics Consultant

Tulsa, OK · On-site

$102K/yr

... Data Mining or related field and 6-8 years of experience in Human Resources or HRIS or 10-12 years of equivalent work experience. * Experience preparing, managing, and analyzing data joined from ...

Senior Workforce Analytics Consultant

Tulsa, OK · On-site

$106K/yr

... Data Mining or related field and 6-8 years of experience in Human Resources or HRIS or 10-12 years of equivalent work experience. * Experience preparing, managing, and analyzing data joined from ...

Reliability Technician

Pryor, OK · On-site

$88K - $111K/yr

Ability to collect, analyze, and interpret equipment performance data. * Strong communication and problem-solving skills. Preferred Heavy Industrial Experience * Cement/Lime * Mining * Aggregates ...

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Mining Data Analytics information

What is the difference between Mining Data Analytics vs Data Analyst?

AspectMining Data AnalyticsData Analyst
Required CredentialsBachelor's in Data Science, Mining Engineering, or related fields; certifications in data analytics or mining softwareBachelor's in Statistics, Data Science, or related fields; certifications in data analysis tools
Work EnvironmentMining sites, data centers, or corporate offices; focus on mineral extraction dataOffice settings, corporate or consulting firms; focus on business data
Employer & Industry UsageMining companies, resource extraction industriesVarious industries including finance, healthcare, retail

Mining Data Analytics and Data Analysts both analyze data, but Mining Data Analytics specializes in mineral extraction data within the mining industry, often requiring industry-specific knowledge and certifications. Data Analysts have a broader scope across multiple industries, focusing on business insights. While both roles involve data interpretation, their environments and applications differ significantly.

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Full-time

Re-posted 14 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

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