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Weekend Data Science Jobs in Louisiana (NOW HIRING)

Cleco

Asset Management Data Analyst

Pineville, LA

This position bridges the gap between Asset Management, Generation Operations, Generation Services, Energy Operations, Corporate Data Analytics/Data Science, and IT to meet business objectives. Key ...

PVI Holdings

Data Systems Engineer

Baton Rouge, LA · On-site

$109K - $132K/yr

Bachelor's degree in Information Systems, Data Engineering, Data Science, or a related field, or equivalent relevant experience * 5+ years of experience writing complex SQL queries and working with ...

The Mutual Group

Actuarial Data Engineer

Iowa, LA · On-site +1

$91K - $130K/yr

The Actuarial Data Engineer will partner with actuarial, data science, and finance teams to deliver reliable and well-structured data solutions that support analytical workflows and business insights.

Jobtailor

AI Data Scientist

Bossier City, LA · On-site

$120 - $160/hr

Architect scalable data pipelines and develop intuitive front‑end experiences using Next.js * Translate intricate technical and analytical insights into clear presentations for leadership

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All JobsData Science JobsWeekend Data Science JobsWeekend Data Science Jobs in Louisiana

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

Asset Management Data Analyst

Cleco Corporate Holdings LLC

Pineville, LA • On-site

Other

Posted 14 days ago

Job description

At Cleco, we're not just powering lives-we're powering a cleaner, smarter future for Louisiana. With bold investments in innovative energy solutions, we're transforming how we power our communities: smarter, cleaner, and more sustainable. This is a long-term commitment to our people and our communities because our future-and the future of generations to come-depends on it. If you're ready to make an impact where it matters most, join us at Cleco-where we're Energizing Your Tomorrow.
The Asset Management Data Analyst II is an experienced professional responsible for integrating plant operational and commercial data & analytics into business processes to optimize generation asset performance. This position will leverage analytical skills, business intelligence expertise, and operational & commercial experience to deliver insights and data solutions that enhance operational efficiency, asset health, maintenance optimization, and commercial performance through various means including data visualization dashboards. This role will require a deep understanding of time series data, data governance & integrity strategies, its integration with business data, and its application in monitoring plant performance and supporting maintenance decision-making. This position bridges the gap between Asset Management, Generation Operations, Generation Services, Energy Operations, Corporate Data Analytics/Data Science, and IT to meet business objectives.
Key Responsibilities
  • Champions a corporate culture that emphasizes transparency, integrity, safety, environmental responsibility, employee development, sense of belonging, customer service, and operational excellence.
  • Accelerate the development and implementation of data analytics to support business decision-making.
  • Gather and analyze operational and commercial data to identify trends, patterns, and insights.
  • Monitor and report on the progress of analytics and data management initiatives.
  • Stay up-to-date with industry trends and best practices in data analysis to continuously improve asset performance
  • Collaborate with generation plant teams to understand data requirements, focusing on time series data from operational systems and integrating it with business data for comprehensive insights.
  • Develop and maintain dashboards, reports, and visualizations using BI tools (e.g., Power BI, Tableau) to support operational performance, asset health monitoring, and maintenance strategy development.
  • Analyze time series data to identify trends, anomalies, and opportunities for optimizing equipment performance and improving reliability.
  • Work with plant teams to model asset health metrics and KPIs that inform predictive maintenance and lifecycle strategies.
  • Support data quality initiatives by ensuring time series data is accurate, reliable, and consistent.
  • Participate in the development and optimization of analytics processes, including the integration of operational and business data.
  • Design and maintain data workflows and pipelines, with a focus on ensuring real-time or near-real-time availability of time series data.
  • Collaborate with enterprise data teams to align local plant data strategies with broader enterprise initiatives, including data governance and architecture.
  • Assist in defining roadmap for AI/ML in asset management including anomaly detection methods and digital twin simulations
  • Architect and utilize Azure-based data analytics platform for scalable model development and deployment.

Qualifications
Required Education, Skills & Experience
  • Bachelor's degree in Information Systems, Data Analytics, Computer Science, Engineering, or a related field.
  • 3 - 8 years of experience in a data analytics or business intelligence role preferred.
  • Hands-on experience with BI tools (e.g., Power BI, Tableau, Qlik, etc.) and proficiency in SQL.
  • Experience working with time series data from SCADA systems, IoT devices, or other industrial data sources.
  • Experience in data integration and workflow optimization, particularly in combining operational and business datasets.
  • Strong analytical and problem-solving skills.
  • Strong experience in generation / commercial operations.
  • Proficiency in data visualization tools (e.g., Power BI) to create dashboards and reports.
  • Knowledge of data management practices and tools.
  • Excellent communication and presentation skills.
  • Ability to work collaboratively with cross-functional teams.
  • Strong organizational and project management skills.
  • Understanding of asset health metrics, predictive maintenance strategies, and their role in enhancing operational efficiency.
  • Familiarity with enterprise data concepts such as data governance, data quality, and data architecture is a strong plus.
  • Ability to translate complex data into insights that support asset health management and maintenance strategies.
  • Experience with Azure data science and big data services (such as Azure Databricks, Azure Machine Learning, Azure Data Lake) or similar cloud platforms (AWS/Google Cloud Platform)
  • Progression to this level is strictly restricted based on critical individual capabilities and business requirements; must be supported by market survey data

Licenses and Certifications
  • Relevant certifications (e.g., Certified Business Analysis Professional (CBAP), Power BI Data Analyst Associate Certification) are a plus but not required.

Key Competencies
BEHAVIORAL
  • Building Partnerships
  • Leading Teams
  • Business Acumen
  • Communication
  • Courage
  • Building Self-Insight
  • Driving for Results
  • Energizing the Organization
  • Driving Execution
  • Building Trusting Relationships
  • Driving Innovation
  • Planning and Organizing
  • Safety
  • Establishing Strategic Direction

TECHNICAL
  • Analytical skills
  • Organizational skills
  • Strategic Planning
  • Data Collection and Analysis
  • Presentation Skills
  • Business Intelligence skills

May perform other duties as assigned.
Salary dependent on experience, skills, education, and training.

Apply