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Quantitative Data Engineer Jobs in Indiana (NOW HIRING)

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Quality Engineer

Seymour, IN · On-site

$62K - $80K/yr

Complete quantitative reports on quality issues and effectively communicate to management. * Lead ... Analyze data to assist with Kaizen activities 1st pass yield, scrap reduction, process improvements ...

New

Guidehouse

Model Validation Lead

Indianapolis, IN

... Engineering, Economics, or a related quantitative field * FIVE (5) or more years of experience in model validation, model risk management, data science, quantitative analysis, or advanced analytics

BC Forward

Data Analyst V - CX or VoC

Indianapolis, IN · On-site +1

$58 - $65/hr

Degree in Analytics, Statistics, Mathematics, Computer/Data Science, Engineering, or related field ... D. in a quantitative field. Familiarity with consumer electronics or retail business. Experience ...

Elevance Health

Gen AI Engineer

Indianapolis, IN · Hybrid

Applies data extraction, transformation and loading techniques in order to connect large data sets ... Requires a Bachelor's degree in a highly quantitative field (Computer Science, Machine Learning ...

JLL

Data Collection Specialist II

Indianapolis, IN · Remote

Bachelor's degree (BA/BS) in engineering, construction management, sciences, IT, or related field a ... Requires analytical and quantitative skills with proven experience in developing strategic ...

Elevance Health

Gen AI Engineer

Indianapolis, IN · Hybrid

Applies data extraction, transformation and loading techniques in order to connect large data sets ... Requires a Bachelor's degree in a highly quantitative field (Computer Science, Machine Learning ...

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Quantitative Data Engineer information

What is an example of quantitative?

A quantitative example involves numerical data that can be measured and analyzed statistically. In a Quantitative Data Engineer role, this might include metrics like transaction volumes, data throughput, or statistical summaries used to build data pipelines and models.

What is quantitative vs qualitative?

Quantitative data refers to numerical information that can be measured and analyzed statistically, such as sales figures or sensor readings. Qualitative data involves descriptive, non-numerical information like opinions, interviews, or observations. In data engineering, understanding both types helps in designing systems that process and analyze diverse data sources effectively.

What are the key skills and qualifications needed to thrive as a Quantitative Data Engineer, and why are they important?

To excel as a Quantitative Data Engineer, you need strong proficiency in programming (such as Python, R, or C++), advanced mathematical and statistical knowledge, and a relevant degree in computer science, mathematics, or a related field. Experience with big data tools (like Spark, Hadoop), cloud platforms, and data pipeline systems, as well as familiarity with financial data sets, is typically required. Analytical thinking, detail orientation, and effective problem-solving skills distinguish top performers in this role. These competencies are critical for efficiently transforming complex data into actionable insights and supporting robust quantitative models in data-driven environments.

What does quantitative mean?

In the context of a Quantitative Data Engineer role, 'quantitative' refers to working with numerical data and statistical methods to analyze and model information. This involves skills in mathematics, programming, and data analysis tools to develop algorithms and insights from large datasets.

What is a Quantitative Data Engineer?

A Quantitative Data Engineer is a professional who designs, builds, and maintains data infrastructure that supports quantitative analysis, typically in finance or technology sectors. They work closely with quantitative analysts and data scientists to ensure efficient data pipelines, data quality, and high-performance systems for processing large datasets. Their responsibilities include developing ETL processes, optimizing databases, and implementing data models to support research and trading strategies. Strong programming skills, expertise in big data technologies, and knowledge of quantitative methods are essential for this role.

What are the synonyms of quantitative?

Synonyms of quantitative include numerical, measurable, and statistical. In a data engineering context, these terms relate to data that can be quantified and analyzed using tools like SQL, Python, or R, often involving numerical datasets and statistical methods.

What is the difference between Quantitative Data Engineer vs Data Scientist?

AspectQuantitative Data EngineerData Scientist
Primary FocusBuilding data pipelines, data infrastructure, and ensuring data qualityAnalyzing data, creating models, and deriving insights
Skills & ToolsSQL, Python, Spark, ETL processes, data architectureStatistics, machine learning, Python/R, data visualization
CredentialsComputer science, engineering, or related degrees; certifications in data engineeringStatistics, data science, or related degrees; certifications in data analysis or machine learning
Work EnvironmentData engineering teams, data infrastructure projectsData analysis teams, research, and modeling projects

While both roles work closely with data, Quantitative Data Engineers focus on building and maintaining data systems, whereas Data Scientists analyze data to generate insights and models. They often collaborate but have distinct skill sets and responsibilities within data-driven organizations.

How does a Quantitative Data Engineer typically collaborate with data scientists and quantitative analysts on projects?

Quantitative Data Engineers work closely with data scientists and quantitative analysts to design, build, and optimize data pipelines that support complex modeling and analytics. They are often responsible for ensuring data quality, scalability, and efficient data processing, enabling analysts to focus on developing models and extracting insights. Regular collaboration includes translating analytical requirements into technical solutions, troubleshooting data issues, and iterating on data infrastructure to support evolving project needs. This teamwork fosters an environment where technical and analytical expertise complement each other, leading to more robust and actionable results.
What are popular job titles related to Quantitative Data Engineer jobs in Indiana? For Quantitative Data Engineer jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Quantitative Data Engineer jobs in Indiana look for? The top searched job categories for Quantitative Data Engineer jobs in Indiana are:
What cities in Indiana are hiring for Quantitative Data Engineer jobs? Cities in Indiana with the most Quantitative Data Engineer job openings:
Quantitative Data Engineer jobs near you
Director of Marketing Analytics and Data Science (Digital Marketing Leader)

Director of Marketing Analytics and Data Science (Digital Marketing Leader)

Indiana University

Bloomington, IN • On-site

Full-time

Medical, Dental, Life, Retirement, PTO

Posted 16 days ago

Job description

Indiana University is seeking a Director of Marketing Analytics and Data Science to drive institutional outcomes by leading the use of data and analytics in designing, measuring, and improving audience experiences across a complex, multi-campus environment. Positioned within the Web and Digital Strategy team within University Communications and Marketing (UCM), this role collaborates closely with experts in marketing and communications, information technology, and higher education to ensure experiences are intentionally designed and informed by data.
Department Specific Responsibilities
  • Reports to the Executive Director of Web and Digital Strategy, the Director of Audience Experience leads the Audience Experience (AX) function.
  • Responsible for omnichannel audience insights, analytics, research, and forecasting.
  • Advances IU's experience engineering and data strategy by transforming data from a reporting function into a strategic capability enabling predictive and prescriptive analytics that guide university strategy, inform decisions, and drive outcomes such as enrollment, engagement, retention, and revenue.
  • Provides strategic leadership within UCM, ensuring data is translated into clear, actionable guidance that supports institutional goals and decision-making.
  • Builds and advances an analytics maturity model-leading a transition from descriptive and diagnostic analytics to predictive and prescriptive analytics, including forecasting, modeling, and outcome-oriented recommendations.
  • Operationalizes IU's experience engineering framework by aligning data with constituent lifecycle stages, triggers, gates, and customer journey orchestration across owned and paid channels.
  • Collaborates with subject matter experts across marketing functions to understand business needs and improve the ability to measure and optimize work.
  • Evangelizes a culture of data strategy and curiosity across the organization.
  • Applies advanced quantitative and analytical techniques (e.g., regression analysis, statistical modeling, A/B testing, multivariate experiments) to complex, multi-source datasets to understand audience behavior, performance, and opportunity.
  • Leads and develops a multidisciplinary Audience Experience team, including data engineering and data visualization specialists, fostering analytical rigor, collaboration, and continuous improvement.
  • Partners with staff to ensure scalable data pipelines, Extract, Transform, Load (ETL) processes, and centralized access to channel, audience, and institutional data that support segmentation, personalization, visualization, and analysis.
  • Collaborates across UCM, campuses, and functional areas to align analytics priorities, enable shared understanding of performance, and support insight-driven planning and investment.
  • Champions ethical, compliant, and responsible data practices, including data governance, privacy, security, and quality standards.
  • Monitors and leads through emerging trends in analytics, data science, and AI to inform continuous improvement and future-state strategy (cookie-less ecosystem, ubiquity of AI, etc.).
General Responsibilities
  • Directs operations for the digital marketing function by providing oversight and direction within a department, large multi-faceted department, or multiple departments.
  • Hires, trains, evaluates, coaches, assigns work, sets goals and objectives, determines staffing needs, and directs the work of a team of digital marketing staff.
  • Manages relationships with various internal and external stakeholders; determines digital marketing needs, projects, and programs to align with objectives and goals and manages processes such as the development of communications timelines related to such initiatives.
  • Reviews drafts of digital marketing strategies, content, and projects and coaches on grammar, tone, branding guidelines, formatting, and other elements that may affect the perception of messaging or reputation of the department.
  • Responds to escalated and complex inquiries and requests and explains policies, procedures, and context of communications.
  • Assists in budget planning and administration for digital marketing initiatives, including expenditures, revenue projections, and program costs.
  • Monitors industry trends and best practices, makes process and operational and strategic recommendations to manager, and assists in implementing recommendations to optimize operations and progress toward objectives.
  • May provide guidance to lower-level Digital Marketing Leaders.
Qualifications
Combinations of related education and experience may be considered. Education beyond the minimum required may be substituted for work experience. Work experience beyond the minimum required may be substituted for education.
EDUCATION
Required
  • Bachelor's degree in communications, journalism, English, public relations, data science, computer science, informatics, information systems, marketing, or related fields.
Preferred
  • Master's degree in data science, computer science, informatics, information systems, marketing, or related fields.
WORK EXPERIENCE
Required
  • 4 years in relevant field.
  • 1 year of management experience in relevant field.
Preferred
  • 7 years of progressive responsibility in analytics, data strategy, audience insights, or a related field within a complex organization.
SKILLS
Required
  • Proficient communication skills.
  • Maintains a high degree of professionalism.
  • Demonstrates time management and priority setting skills.
  • Demonstrates a high commitment to quality.
  • Excellent organizational skills.
  • Excellent collaboration and team building skills.
  • Effectively coaches and delivers constructive feedback.
  • Instills commitment to organizational goals.
  • Demonstrates excellent judgment and decision making skills.
  • Effective conflict management skills.
  • Builds and manages effective teams.
Preferred
  • Advanced quantitative and analytical skills, with demonstrated experience performing regression analysis, forecasting, statistical modeling, and multivariate analysis.
  • Strong understanding of analytics maturity models and the ability to guide organizations from reporting-focused analytics toward insight-, foresight-, and outcome-driven decision-making.
  • Ability to connect analytical work to concrete business or institutional outcomes, including revenue generation, enrollment, retention, and engagement.
  • Strong systems-thinking mindset, with the ability to integrate data across marketing channels, Customer Relationship Management (CRM) platforms, and institutional systems.
  • Familiarity with digital marketing and audience data ecosystems (e.g., GA4, CRM/CDP platforms, marketing automation, data visualization tools).
  • Data storytelling the ability to translate complex analytical findings into clear, compelling narratives and recommendations for senior leaders and non-technical stakeholders .
  • Demonstrated success leading through influence and partnership in decentralized or matrixed environments.
  • Experience leading or mentoring multidisciplinary teams that include analytics, data engineering, and data visualization roles.
  • Familiarity with higher education context.
Working Conditions / Demands
This role requires the ability to effectively communicate and to operate a computer and other standard office productivity equipment. The position involves sedentary work as well as periods of time moving around an office environment and the campus. The person in this role must be able to perform the essential functions with or without an accommodation.
Work Location
Bloomington, Indiana or Indianapolis, Indiana.
Benefits Overview
For full-time staff employees, Indiana University offers a wide array of benefits including:
  • Comprehensive medical and dental insurance
  • Health savings account with generous IU contributions
  • Healthcare and dependent care flexible spending accounts
  • Basic group life insurance paid by IU
  • Voluntary supplemental life, long-term disability, critical illness, and supplemental accidental death & dismemberment insurance
  • Base retirement plan with generous IU contributions, subject to vesting
  • Voluntary supplemental retirement plan options
  • Tuition subsidy for employees and family members taking IU courses
  • 10 paid holidays plus a paid winter break each year
  • Generous paid time off plans
  • Paid leave for new parents and IU-sponsored volunteer events
  • Employee assistance program (EAP)
Learn more about our benefits by reviewing the IU Benefit Programs Brochure .
Job Classification
Career Level: Sr. Operational
FLSA: Exempt
Job Function: Marketing & Communications
Job Family: Digital Marketing
Click here to learn more about Indiana University's Job Framework.
Posting Disclaimer
This posting is scheduled to close at 11:59 pm EST on the advertised Close Date. This posting may be closed at any time at the discretion of the University, but will remain open for a minimum of 5 business days. To guarantee full consideration, please submit your application within 5 business days of the Posted Date.
If you wish to include a cover letter, you may include it with your resume when uploading attachments.
Equal Employment Opportunity
Indiana University is an equal opportunity employer and provider of ADA services and prohibits discrimination in hiring. See Indiana University Notice of Non-Discrimination here which includes contact information .
Campus Safety and Security
The Annual Security and Fire Safety Report, containing policy statements, crime and fire statistics for all Indiana University campuses, is available online . You may also request a physical copy by emailing IU Public Safety at iups@iu.edu or by visiting IUPD.
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