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Weekend Data Science Jobs in Schenectady, NY (NOW HIRING)

Versant Health

Senior Data Scientist

Troy, NY · On-site

This role operates at the intersection of data science, data engineering, cloud analytics platforms, and business strategy, serving as a technical authority and thought leader across complex, high ...

Versant Health, Inc.

Senior Data Scientist

Troy, NY · On-site

$150 - $210/hr

This role operates at the intersection of data science, data engineering, cloud analytics platforms, and business strategy, serving as a technical authority and thought leader across complex ...

Brookfield

Sr P&C Data Scientist

Albany, NY · On-site

Five years of relevant experience in data science, analytics, pricing, actuarial, or related quantitative roles. A master's degree may be considered in lieu of one to two years of experience

Kayla's HR Co

Assistant Manager

Schenectady, NY · Remote

Senior Data Scientist - Machine Learning Specialist We are seeking a talented and innovative Senior Data Scientist to join our growing analytics team. In this impactful role, you will leverage your ...

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All JobsData Science JobsWeekend Data Science JobsWeekend Data Science Jobs in Schenectady, NY

Weekend Data Science information

See Schenectady, NY salary details

$36.3K

$118.8K

$190.1K

How much do weekend data science jobs pay per year?

As of Sep 5, 2026, the average yearly pay for weekend data science in Schenectady, NY is $118,753.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,300.00 and $131,600.00 per year, depending on experience, location, and employer.

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 Schenectady, NY?

The most popular types of Data Science jobs in Schenectady, NY are:

What are popular job titles related to Weekend Data Science jobs in Schenectady, NY?

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

What job categories do people searching Weekend Data Science jobs in Schenectady, NY look for?

The top searched job categories for Weekend Data Science jobs in Schenectady, NY are:

What cities near Schenectady, NY are hiring for Weekend Data Science jobs?

Cities near Schenectady, NY with the most Weekend Data Science job openings:

Weekend Data Science jobs near you

Senior Data Scientist

Versant Health

Troy, NY • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 18 days ago

Job description

Senior Data Scientist
Senior Data Scientist
Who are we?
Versant Health is one of the nation's leading administrators of managed vision care, serving millions of our clients' members nationwide. We are driven by our mission to help members enjoy the wonders of sight through healthy eyes and vision.
As a Versant Health associate, you can enjoy a comprehensive Total Rewards package, which includes health and dental insurance, tuition reimbursement, 401(k) with company match, pet insurance, no-cost-to-you vision insurance for you and your qualified dependents. We are also invested in your success. There are many opportunities for advancement and development throughout all stages of your career with us.
See how you can make a difference with the support of strong leadership and a team environment.
See Everything, Be Anything™.
What are we looking for?
The Senior Data Scientist is a principal-level individual contributor responsible for architecting, delivering, and governing enterprise-grade advanced analytics and machine learning solutions that materially influence strategic decisions, financial performance, operational efficiency, and regulatory posture.
This role operates at the intersection of data science, data engineering, cloud analytics platforms, and business strategy, serving as a technical authority and thought leader across complex, high-risk analytical initiatives-particularly within regulated healthcare environments.
The Senior Data Scientist is accountable not only for model development, but for explainability, stability, auditability, and long-term operational viability of analytical solutions deployed at scale within the Microsoft data ecosystem.
Where you will have an impact
  • Architect, design, and deploy advanced statistical, predictive, and machine learning solutions that support enterprise-level decision-making across healthcare, operations, finance, and customer/member domains.
  • Own end-to-end analytical solution lifecycle, including data discovery, feature engineering, modeling, validation, performance monitoring, retraining strategy, and retirement planning.
  • Serve as a technical authority on model explainability, fairness, robustness, and regulatory defensibility-particularly where ground truth or forward-looking forecasts are limited.
  • Design analytics solutions natively within the Microsoft cloud analytics stack, ensuring alignment to enterprise data architecture and governance standards.
  • Partner closely with executive stakeholders, data engineering leaders, and platform owners to translate complex business questions into high-impact, production-ready analytics.
  • Lead and influence analytics standards without direct authority.
  • Define best practices for: model documentation, audit artifacts, model risk management, stability analysis, reproducibility, and controlled experimentation.
  • Guide and review work produced by other data scientists, analysts, and vendors to ensure technical rigor and business relevance.
  • Present complex analytical findings to senior leadership using clear narratives, decision-oriented visuals, and quantified trade-offs.
  • Proactively identify analytical risks, data limitations, and downstream impacts of modeling decisions.
  • Continuously evaluate emerging tools, methodologies, and Microsoft platform capabilities to drive modernization and performance gains.

What's necessary to do the job?
  • Master's degree preferred in data science, statistics, mathematics, computer science, engineering, or related field required.
  • 7-10+ years of progressive experience delivering advanced analytics or machine learning solutions in complex, data-rich environments.
  • Required: Prior experience in healthcare analytics (payer, provider, life sciences, or regulated healthcare data domains).
  • Prior acutrary experience a plus.
  • Proven experience deploying production analytics or ML solutions supporting mission-critical business processes.
  • Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow where appropriate)
  • SQL (advanced T-SQL optimization, analytical patterns)
  • ML explainability and governance techniques (e.g., SHAP-style approaches, stability testing)
  • Deep, hands-on, production experience across sizable portion of the Microsoft analytics ecosystem, including:
  • Microsoft Fabric (Lakehouse, Data Warehouse, Real-Time Analytics, Notebooks)
  • Azure Synapse Analytics (dedicated & serverless SQL pools)
  • Azure Data Factory (Fabric Data Pipelines)
  • Azure Data Lake Storage
  • Azure Machine Learning (model training, deployment, monitoring)
  • Power BI (semantic models, DAX optimization, executive dashboards)
  • Microsoft Purview (data cataloging, lineage, classification)

HIPAA & Security Requirements
All Associates must comply with the Health Insurance Portability Accountability Act of 1996 (HIPAA) as it pertains to disclosures of protected health information (PHI) as described in the Notice of Privacy Practices and HIPAA Privacy Policies and Procedures. As a component of job roles and responsibilities, Associates may have access to covered information, cardholder data or other confidential customer information which must be protected at all times. As a result, Associates must explicitly adhere to all data security guidelines established within the Company's Privacy & Security Training Program.
We offer a comprehensive and competitive total rewards package designed to support your health, financial well-being, and work-life balance. Benefits include medical, dental, and paid vision coverage; paid time off and company holidays; retirement savings with employer contribution; employee wellness resources; and professional development opportunities. Additional benefits may include flexible work arrangements, employee assistance programs, and other programs that support you both at work and beyond.
Versant Health will never request money from candidates who seek employment with us and will never ask for any payment as part of the recruitment process.
Versant Health is a proud Equal Employment Opportunity and Affirmative Action employer dedicated to attracting, retaining, and developing a diverse and inclusive workforce. All qualified applicants will receive consideration for employment at Versant Health without regards to race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity or expression, age, disability, national origin, marital or domestic/civil partnership status, genetic information, citizenship status, uniformed service member or veteran status, or any other characteristic protected by law.

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