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Manager Predictive Analytics Jobs in Missouri (NOW HIRING)

Enterprise Holdings

Data Scientist

Saint Louis, MO · On-site

$85 - $115/hr

Louis, Enterprise Mobility together with its affiliate Enterprise Fleet Management manages a ... Perform exploratory data analysis to identify patterns, trends, and insights * Develop predictive ...

Enterprise Holdings

Data Scientist

Saint Louis, MO · On-site

Louis, Enterprise Mobility together with its affiliate Enterprise Fleet Management manages a ... Perform exploratory data analysis to identify patterns, trends, and insights * Develop predictive ...

Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps ... Excellent analytical, problem-solving, and communication skills. * Professional working proficiency ...

Enterprise Holdings

Data Scientist

Saint Louis, MO · On-site

Louis, Enterprise Mobility together with its affiliate Enterprise Fleet Management manages a ... Perform exploratory data analysis to identify patterns, trends, and insights * Develop predictive ...

Inland Empire Health Plan

Data Scientist II

California, MO · On-site

$118.60 - $157.14/hr

Apply descriptive and predictive analytics to help drive insights and business decisions. * Apply a ... Manage tests for specific providers and generate data to build out case studies and messaging ...

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Showing results 21-40

All JobsPredictive Analytics JobsManager Predictive Analytics JobsManager Predictive Analytics Jobs in Missouri

Manager Predictive Analytics information

What are the key skills and qualifications needed to thrive as a manager predictive analytics?

To thrive as a Manager Predictive Analytics, you need a strong background in statistics, data analysis, and predictive modeling, often supported by a degree in mathematics, statistics, computer science, or a related field. Expertise with analytics tools such as Python, R, SQL, and familiarity with machine learning platforms, as well as relevant certifications like SAS or AWS Certified Machine Learning, is typically expected. Outstanding leadership, communication, and problem-solving skills help in leading teams and translating complex insights for stakeholders. These abilities ensure data-driven decision-making, effective project management, and impactful business outcomes.

What are the main challenges faced by a manager predictive analytics, and how can they be addressed?

A Manager of Predictive Analytics often encounters challenges such as ensuring data quality, bridging communication gaps between technical teams and business stakeholders, and keeping up with rapidly evolving analytical tools and techniques. Addressing these challenges requires fostering strong cross-functional collaboration, implementing robust data governance practices, and encouraging continuous learning among team members. Additionally, setting clear project objectives and maintaining alignment with business goals can help deliver actionable insights and maximize the impact of predictive analytics initiatives.

What is the difference between Manager Predictive Analytics vs Data Scientist?

AspectManager Predictive AnalyticsData Scientist
Required CredentialsBachelor's or Master's in Analytics, Statistics, or related field; often managerial certificationsBachelor's or Master's in Data Science, Statistics, or related field; sometimes PhDs
Work EnvironmentLeads teams, manages projects, collaborates with business unitsDevelops models, analyzes data, experiments with algorithms
Employer & Industry UsageBusiness, finance, marketing, healthcare organizationsTech companies, research institutions, finance, healthcare

While both roles focus on data analysis, the Manager Predictive Analytics oversees teams and strategic projects, whereas Data Scientists primarily develop models and conduct in-depth data analysis. The manager role emphasizes leadership and project management, often requiring experience in analytics tools and business acumen, while Data Scientists focus on technical expertise in algorithms and programming.

What is a manager predictive analytics?

A Manager Predictive Analytics is a professional responsible for overseeing teams and projects that use statistical techniques, machine learning, and data analysis to forecast future trends and support business decision-making. They manage the development and implementation of predictive models, ensuring data quality and actionable insights for their organization. In addition to technical expertise, they coordinate with stakeholders to align analytics initiatives with business goals and often mentor data analysts or data scientists within their team.

What are the most commonly searched types of Predictive Analytics jobs in Missouri?

The most popular types of Predictive Analytics jobs in Missouri are:

What are popular job titles related to Manager Predictive Analytics jobs in Missouri?

For Manager Predictive Analytics jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Manager Predictive Analytics jobs in Missouri look for?

The top searched job categories for Manager Predictive Analytics jobs in Missouri are:

What cities in Missouri are hiring for Manager Predictive Analytics jobs?

Cities in Missouri with the most Manager Predictive Analytics job openings:

Manager Predictive Analytics jobs near you
Infographic showing various Manager Predictive Analytics job openings in Missouri as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution.

Senior Data Engineer - Oil, Gas & Chemical (Kansas City)

Burns & McDonnell

Kansas City, MO • On-site

$103K - $140K/yr

Full-time

Posted 9 days ago

Burns & McDonnell rating

8.7

Company rating: 8.7 out of 10

Based on 50 frontline employees who took The Breakroom Quiz

3rd of 80 rated construction

Job description

Description
The Senior Data Engineer is responsible for leading the development of scalable, data-driven solutions that enable trusted business intelligence, analytics, and enterprise data products across the Oil, Gas and Chemical (OGC) Global Practice. This role partners with engineering, construction, business, data engineering, and technology stakeholders to establish reliable data foundations that support strategic decision-making and operational excellence.
This position serves as a technical leader in advancing the organization's Databricks-based data ecosystem through modern data engineering practices, analytics, governance, and data product development. The role is responsible for designing and optimizing data pipelines, implementing data quality controls, managing enterprise data transformations, and enabling scalable solutions that support reporting, business intelligence, and analytical initiatives.
The Senior Data Engineer establishes and promotes best practices for data management, governance, metadata management, lifecycle controls, and analytical solution development while supporting the organization's long-term data strategy. Machine learning, predictive analytics, and advanced statistical techniques may be applied where appropriate to deliver measurable business value and improve decision-making capabilities.
Key Responsibilities:
Data Platform and Data Engineering
  • Lead the design, development, implementation, and support of scalable data pipelines, orchestration frameworks, and data transformation processes utilizing the Databricks platform.
  • Design, develop, and optimize Databricks notebooks, workflows, Delta Lake architectures, and enterprise data products to support business and project delivery needs.
  • Oversee the collection, ingestion, cleansing, transformation, validation, and quality control of structured and unstructured data assets.
  • Implement database-layer transformations, query optimization strategies, and automated quality controls to support a high-performance shared data environment.
  • Partner with architects, developers, and data engineers to align solutions with enterprise architecture, governance standards, and platform best practices.

Data Governance and Data Products
  • Establish and promote data governance standards, including data ownership, lifecycle management, metadata management, and data quality controls.
  • Lead implementation of enterprise data quality frameworks and validation processes to ensure trusted and consistent data assets.
  • Develop and maintain enterprise data flow documentation that visualizes data origins, transformations, dependencies, and downstream consumption across systems.
  • Lead the development and lifecycle management of enterprise data products supporting analytics, reporting, operational processes, and business decision-making.
  • Support Code of Account (COA) mapping initiatives by identifying, modeling, validating, and governing quantity and cost-related data relationships across estimating, engineering, procurement, and construction systems.

Analytics and Business Intelligence
  • Analyze data to discover business value, trends, relationships, and opportunities that support strategic business initiatives and operational improvements.
  • Develop dashboards, reports, and visualizations utilizing Power BI and related technologies to communicate technical results and business insights.
  • Perform root cause analysis, trend analysis, and analytical investigations to support business performance and process improvement.
  • Apply machine learning, predictive analytics, and statistical techniques where appropriate to solve business problems and improve decision-making outcomes.

Leadership and Collaboration
  • Partner with engineering, construction, project delivery, and business stakeholders to understand data requirements and improve enterprise data maturity.
  • Evaluate emerging platform technologies, analytical capabilities, industry practices, and data solutions for applicability to business challenges and opportunities.
  • Train and mentor less experienced data professionals and business data users. Provide performance feedback to managers.
  • Participate in recruitment efforts and technical candidate evaluations.
  • Other duties, as assigned.

Qualifications
  • Bachelor's degree in Analytics, Computer Science, Information Systems, Statistics, Mathematics, Engineering, or a related field; and a minimum of 8 years of related experience.
  • Experience designing, developing, deploying, and supporting production solutions within Databricks environments strongly preferred.
  • Strong knowledge of Databricks Lakehouse architecture, Delta Lake, Unity Catalog, Databricks Workflows, and Databricks notebooks strongly preferred.
  • Experience implementing governance, security, metadata management, and data lifecycle processes within enterprise data platforms strongly preferred.
  • Experience with Databricks, Python, SQL, and modern data engineering practices.
  • Experience developing, supporting, and optimizing scalable data pipelines, orchestration frameworks, and cloud-based data solutions.
  • Knowledge of data governance frameworks, metadata management, data quality methodologies, and lifecycle management practices.
  • Experience leading data mining, advanced analytics, machine learning, predictive analytics, and statistical modeling initiatives.
  • Experience developing enterprise data products and analytical solutions that support business intelligence and operational processes.
  • Experience with Power BI or similar data visualization and reporting technologies.
  • Experience with GCP BigQuery or similar cloud data warehouse technologies is preferred.
  • Familiarity with engineering, construction, project delivery, asset, or related technical data environments is preferred.
  • Ability to collaborate effectively with business stakeholders, architects, developers, data engineers, and application teams.
  • Ability to translate complex data ecosystems into practical, scalable, and sustainable enterprise solutions.
  • Strong problem-solving and analytical skills.
  • Strong attention to detail and commitment to data quality.
  • Excellent verbal and written communication skills with the ability to present technical concepts and findings to business audiences.

This job posting will remain open a minimum of 72 hours and on an ongoing basis until filled.
EEO/Disabled/Veterans
Job Scientific
Primary Location US-MO-Kansas City
Schedule: Full-time
Travel: Yes, 10 % of the Time
Req ID: 263549
Job Hire Type Experienced #LI-JJ #OGC

What Burns & McDonnell employees say

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Benefits

Hours and flexibility

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About Burns & McDonnell

Sourced by ZipRecruiter

Burns & McDonnell assists clients of all sizes and industries by providing extensive physical services ranging from assessments, integrated security solutions, and large security architecture designs. Services we typically provide include security and safety system design, threat, risk, and vulnerability assessments, security surveys, security master planning, compliance to federal security programs, independent validation and verification of integrated security system operations, management of installation and maintenance, and staff augmentation to develop and implement facility management and protection processes.

Industry

Civil engineering construction

Company size

10,000+ Employees

Headquarters location

Kansas City, MO, US

Year founded

1898

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