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Statistical Engineering Jobs in Spring, TX (NOW HIRING)

United Global Technologies

IT Data Engineering JG3

Houston, TX · Hybrid

$109K - $131K/yr

... Run statistical/econometric analyses on large datasets (e.g., market & fundamental time series data). · Collaborate directly with traders/analysts--translate ambiguous questions into shippable ...

Hp

Principal Reliability Engineer

Spring, TX

$91K - $114K/yr

You will work cross-functionally with engineering, procurement, supply chain, and Original Design ... Utilize numerical and statistical analysis methods to assess accelerated test and field data ...

SynergisticIT

UI Developer (jQuery + Bootstrap)

Houston, TX · On-site

$47.75 - $62/hr

Recent Computer science/Engineering /Mathematics/Statistics or Science Graduates or People looking to switch careers or who have had gaps in employment and looking to make their careers in the Tech ...

Bridgestone

Senior Engineering Manager

Houston, TX · On-site

Statistical process control is used in every step of the operation. Firestone Polymers, LLC is a ... Job Category Engineering & Science Position Summary The Senior Engineering Manager position has ...

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All JobsStatistical Engineering JobsStatistical Engineering Jobs in Spring, TX

Statistical Engineering information

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

To thrive as a Statistical Engineer, you need strong quantitative analysis skills, a background in statistics or mathematics, and often a relevant degree such as in engineering or applied statistics. Proficiency with statistical software (e.g., R, SAS, Python), data management systems, and sometimes Six Sigma certification is typically required. Critical thinking, problem-solving, and clear communication are crucial soft skills for interpreting data and collaborating with multidisciplinary teams. These skills ensure accurate data-driven decisions, efficient process improvements, and effective solutions to complex engineering challenges.

What engineers make $300,000 a year?

Senior statistical engineers or data science leaders with extensive experience, advanced skills in statistical modeling, programming, and data analysis can earn $300,000 or more annually. These roles often require advanced degrees, certifications, and leadership responsibilities in industries like finance, technology, or pharmaceuticals.

What do statistical engineers do?

Statistical engineers develop and implement statistical models and methods to analyze complex data, often focusing on process improvement and quality control. They use tools like statistical software and programming languages such as R or Python and collaborate with data scientists and engineers to optimize systems and decision-making processes.

What engineers make $500,000?

Senior engineers in specialized fields such as software engineering, petroleum engineering, and certain roles in financial engineering can earn $500,000 or more annually, often including bonuses and stock options. High compensation typically requires extensive experience, advanced skills, and working in high-demand industries or leadership positions.

What is the difference between Statistical Engineering vs Data Scientist?

AspectStatistical EngineeringData Scientist
Required credentialsStatistics, Data Analysis, EngineeringStatistics, Computer Science, Data Analysis
Work environmentManufacturing, R&D, Engineering teamsBusiness, Tech, Research sectors
Employer usageOptimizing processes, designing experimentsBuilding models, insights, predictive analytics

Statistical Engineering focuses on applying statistical methods to improve engineering processes and product development, often within manufacturing or R&D settings. Data Scientists analyze large datasets to extract insights, build predictive models, and support business decisions. While both roles require strong statistical skills, Statistical Engineering emphasizes process optimization and experimental design, whereas Data Scientists focus on data-driven insights across diverse industries.

How much does a Statistical Engineer make?

The average salary for a Statistical Engineer typically ranges from $70,000 to $120,000 annually, depending on experience, education, and location. Professionals in this role often use statistical software and data analysis tools, and advanced skills can lead to higher compensation.

How does a Statistical Engineer typically collaborate with cross-functional teams to implement data-driven solutions?

Statistical Engineers frequently work alongside data scientists, software engineers, and business analysts to design and implement robust data-driven solutions. They are responsible for translating complex statistical models into actionable insights and ensuring that these models are integrated effectively within existing systems. Collaboration often involves regular meetings to align on project goals, sharing progress updates, and troubleshooting technical challenges together. This interdisciplinary teamwork is essential for ensuring that statistical methodologies are not only theoretically sound but also practically applicable to real-world business problems.

What is statistical engineering?

Statistical engineering is an interdisciplinary field that focuses on the integration and application of statistical methods and principles to solve complex, large-scale problems in science, business, and engineering. It involves designing data collection processes, analyzing and interpreting data, and implementing statistical solutions within larger systems. Statistical engineers often work on projects that require collaboration with other engineering disciplines, using statistics as a foundational tool to drive decision-making and innovation.
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What job categories do people searching Statistical Engineering jobs in Spring, TX look for? The top searched job categories for Statistical Engineering jobs in Spring, TX are:
What cities near Spring, TX are hiring for Statistical Engineering jobs? Cities near Spring, TX with the most Statistical Engineering job openings:
Statistical Engineering jobs near you
IT Data Engineering JG3

IT Data Engineering JG3

United Global Technologies

Houston, TX • Hybrid

$109K - $131K/yr

Full-time

Posted 29 days ago

Job description

We're hiring an AI Engineer with a strong data engineering foundation and excellent communication skills—ideally with commodity or financial trading experience. You'll partner with traders and trading analysts to rapidly build AI powered analytics over market pricing and fundamentals data, using Databricks and Spark to deliver value at speed.

What you'll do

· Design and ship AI driven analytics for front office use (seasonality, correlation, regression, forecasting, scenario modelling).

· Build reusable and scalable data pipelines in Databricks (PySpark/Spark, Delta/Unity Catalog), optimizing cost, reliability, and performance.

· Run statistical/econometric analyses on large datasets (e.g., market & fundamental time series data).

· Collaborate directly with traders/analysts—translate ambiguous questions into shippable solutions; communicate insights clearly.

· Implement LLM/agentic workflows: prompt engineering, LangGraph orchestration, MCP integrations, tool calling, retrieval, and guardrails.

· Productionize solutions with testing, observability, versioning, and documentation.

What you'll bring

· Hands on Databricks + Spark expertise (PySpark, SQL, Delta, Unity Catalog).

· Proven data engineering skills (ingestion, modelling, orchestration, performance tuning).

· Strong statistics/economics/data science fundamentals for market time series.

· Experience building LLM solutions (prompting, retrieval, agent flows; LangGraph, MCP) and integrating with trading data/services.

· Experience with CI/CD, Terraform, MLflow/feature stores, vector DBs, and governance (PII handling, data lineage).

· Excellent stakeholder skills; able to work on desk with traders/analysts and deliver fast.
Nice to have

· Background in commodity or financial trading.

· Familiarity with market microstructure, supply demand fundamentals, risk management.

Ways of working

Hybrid; high touch collaboration with trading teams.

Bias to prototype fast, iterate with users, and harden to production.

Maintain operational stability of production pipelines using secure, modern CI/CD engineering practices — with automated testing, quality gates, and built in reliability across development, security, and operations.