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Weekend Data Science Jobs in Louisiana (NOW HIRING)

CSAA

  • Retirement

Job Title Senior Data Science Consultant, Insurance - Remote Requisition Number R7828 Senior Data Science Consultant, Insurance - Remote (Open) Location Arizona - Home Teleworkers Additional ...

Daikin Applied Americas Inc

Data Scientist III

Iowa, LA · On-site

$90 - $153.30/hr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Bachelor's degree in Data Analytics, Data Science, Computer Science, Applied Mathematics, Engineering, or related field * 5+ years (or 3+ years with a masters) of professional experience in analytics ...

GDIT

AI Data Scientist

Bossier City, LA · On-site +1

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Data Science and Data Engineering Job Qualifications: Skills: AI Systems, Big Data, Datasets Certifications: None Experience: 2 + years of related experience US Citizenship Required: Yes Own your ...

Pwc

Payer Healthcare Data Scientist, Manager

New Orleans, LA · On-site

$99K - $232K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

The Opportunity As part of the Operations Consulting team, you will apply advanced data science and machine learning techniques to large-scale claims, clinical, and member data to surface actionable ...

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Weekend Data Science information

What is a weekend data science?

A Weekend Data Science job typically refers to a part-time or contract-based data science position where the primary work hours are on weekends. These roles are ideal for students, professionals seeking extra income, or those looking to gain experience in the data science field without committing to a full-time weekday schedule. Weekend data scientists analyze data, build models, and generate insights just like full-time data scientists but with flexible or reduced hours that fit around a weekend schedule.

What skills and qualifications are needed to thrive as a weekend data scientist?

To thrive as a Weekend Data Scientist, you need strong analytical skills, proficiency in statistics, and expertise in programming languages such as Python or R, often supported by a degree in a quantitative field. Familiarity with data analysis tools like SQL, machine learning libraries (e.g., scikit-learn, TensorFlow), and data visualization platforms (e.g., Tableau) is typically required. Excellent time management, problem-solving ability, and effective communication are crucial soft skills for delivering insights on tight weekend deadlines. These skills ensure that data-driven decisions can be made efficiently and accurately, even within limited time frames.

What challenges do data scientists working on weekends face, and how can they be managed?

Data scientists working weekend shifts often encounter challenges such as limited access to colleagues for collaboration or support, since many team members may not be available outside standard business hours. Additionally, urgent issues or data anomalies may require quick, independent problem-solving. Proactive communication with weekday teams, thorough documentation, and setting up clear protocols for handoffs can help manage these challenges and ensure smooth workflow continuity.

What is the difference between Weekend Data Science vs Part-Time Data Analyst?

AspectWeekend Data SciencePart-Time Data Analyst
CredentialsTypically requires a degree in data science, statistics, or related fieldOften requires a degree or relevant experience in data analysis or related fields
Work EnvironmentProject-based, flexible hours, often remote or on-site during weekendsFlexible hours, may be remote or on-site, often with less technical complexity
Industry UsageUsed in tech, finance, healthcare, and startups for specialized projectsCommon in retail, marketing, and small businesses for routine data tasks

Weekend Data Science roles focus on complex data projects requiring advanced skills, often during weekends, while Part-Time Data Analysts handle routine data tasks with less technical depth, offering flexible schedules. Both roles serve different needs but share a focus on data work outside standard hours.

Do weekend data scientists work on weekends?

Weekend data scientists may work on weekends depending on project deadlines, company policies, or client needs. Typically, data science roles involve regular weekday hours, but some positions require weekend work, especially in roles with flexible or project-based schedules. It is important to clarify work hours during the hiring process or in job descriptions.

What are the most commonly searched types of Data Science jobs in Louisiana?

The most popular types of Data Science jobs in Louisiana are:

What are popular job titles related to Weekend Data Science jobs in Louisiana?

For Weekend Data Science jobs in Louisiana, the most frequently searched job titles are:

What job categories do people searching Weekend Data Science jobs in Louisiana look for?

The top searched job categories for Weekend Data Science jobs in Louisiana are:

What cities in Louisiana are hiring for Weekend Data Science jobs?

Cities in Louisiana with the most Weekend Data Science job openings:

Weekend Data Science jobs near you

Senior Manager Data Science & AI

Bollinger Shipyards

Raceland, LA • On-site

Full-time

Re-posted 19 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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