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Data Science Jobs in Houma, LA (NOW HIRING)

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Well Testing Data Acquisition Engineer

Houma, LA · On-site

$110K - $132K/yr

The Technical Data Acquisition Engineer located in Houma, Louisiana is responsible for installing, configuring, and operating data acquisition systems to monitor and record operational parameters in ...

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Data Science information

See Houma, LA salary details

$36.3K

$118.7K

$190K

How much do data science jobs pay per year?

As of Aug 22, 2026, the average yearly pay for data science in Houma, LA is $118,661.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,200.00 and $131,500.00 per year, depending on experience, location, and employer.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

Is a data scientist in high demand?

Data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

What jobs can a data scientist do?

A data scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.
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The top searched job categories for Data Science jobs in Houma, LA are:

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Cities near Houma, LA with the most Data Science job openings:

Data Science jobs near you
Infographic showing various Data Science job openings in Houma, LA as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 11% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $118,661 per year, or $57 per hour.

Senior Manager Data Science & AI

Bollinger Shipyards

Raceland, LA • Remote

Full-time

Re-posted 21 days ago

Bollinger Shipyards rating

6.5

Company rating: 6.5 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

Job description

Job Title: Senior Manager Data Science & AI

Location: Remote USA

Position Overview: The Senior Manager, Data Science & AI is responsible for establishing and scaling enterprise artificial intelligence, machine learning, and advanced analytics capabilities across Bollinger Shipyards. This role leads the identification, prioritization, development, and operationalization of AI solutions that improve forecasting, bidding, operational efficiency, planning, and decision-making.

The role partners closely with business leaders, Data Engineering, Analytics, and Enterprise Architecture to ensure AI initiatives are aligned to strategic priorities and successfully integrated into enterprise operations.

Key Responsibilities:

  • ·         Define and execute the enterprise roadmap for AI, machine learning, and advanced analytics initiatives
  • ·         Identify and prioritize high-value AI and predictive analytics use cases aligned to operational and strategic objectives
  • ·         Lead development of models supporting forecasting, cost estimation, scheduling, bidding optimization, operational efficiency, and intelligent automation
  • ·         Establish standards and governance for model development, validation, deployment, monitoring, and lifecycle management
  • ·         Ensure AI and ML solutions are integrated into enterprise workflows and production systems
  • ·         Partner with Data Engineering teams to ensure availability of scalable, high-quality datasets for model development
  • ·         Collaborate with business leaders to drive adoption and measurable business value from AI capabilities
  • ·         Evaluate emerging AI technologies, platforms, and opportunities relevant to Bollinger’s operational environment
  • ·         Lead and develop data science and ML engineering resources
  • ·         Ensure responsible, secure, and compliant use of AI technologies and enterprise data
  • ·         Establish KPIs and performance measures for AI initiatives and operational impact

Qualifications:

•           Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, Mathematics, or related field

•           8+ years of experience in data science, AI, machine learning, or advanced analytics roles

•           3+ years of leadership experience

•           Proven experience leading enterprise AI and ML initiatives from concept through operational deployment

•           Strong background in statistical modeling, machine learning, predictive analytics, and optimization techniques

•           Experience working with large and complex enterprise datasets

•           Experience leading technical teams and enterprise-scale initiatives

Skills and Abilities:

•           Experience in manufacturing, industrial, shipbuilding, engineering, or operational environments

•           Experience with Azure AI, ML Ops, cloud AI platforms, and modern AI frameworks

•           Familiarity with Generative AI, intelligent automation, and agent-based AI applications

•           Experience operationalizing AI solutions within ERP or operational systems

•           Knowledge of AI governance, model risk management, and responsible AI practices

Bollinger is an equal opportunity employer and is committed to providing employment opportunities to minorities, females, veterans and disabled individuals, and without regard to sexual orientation and gender identity.

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