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Weekend First Data Merchant Services Jobs in California

About the role We are hiring Nash's first Data Scientist. You will combine product judgment ... Now products and services come to them, on their terms, in real time. That shift has turned every ...

... B2B, merchant services, POS, SaaS, or field sales experience * Existing local business ... First Data * Modern payments and POS platform built to compete in today's SMB market

... B2B, merchant services, POS, SaaS, or field sales experience * Existing local business ... First Data * Modern payments and POS platform built to compete in today's SMB market

Senior Data Analytics Engineer

San Francisco, CA · On-site

$124K - $169K/yr

They are seeking their first data analytics hire to establish and own the data foundation for their ... services. Founded in 2022, the company is headquartered in Irvine, USA, with a team of 11-50 ...

Sr. Lead Data Analyst, Merchant

Los Angeles, CA · On-site +1

$92K - $116K/yr

Description JOB TITLE: Sr. Lead Data Analyst, Merchant LOCATION: Los Angeles, CA (Hybrid in our ... People choose Sunbit for its people-first culture rooted in service, inclusion, and real-world ...

Sr. Lead Data Analyst, Merchant

Los Angeles, CA · On-site

$92K - $116K/yr

JOB TITLE: Sr. Lead Data Analyst, Merchant LOCATION: Los Angeles, CA (Hybrid in our Westwood Office ... People choose Sunbit for its people-first culture rooted in service, inclusion, and real-world ...

Showing results 21-40

Weekend First Data Merchant Services information

What are the key skills and qualifications needed to thrive as a weekend First Data Merchant Services representative, and why are they important?

To thrive as a Weekend First Data Merchant Services representative, you need strong customer service skills, knowledge of payment processing, and typically a high school diploma or equivalent. Familiarity with payment processing platforms, CRM systems, and basic troubleshooting tools is often required. Excellent communication, problem-solving abilities, and patience help you deliver effective support and resolve merchant issues efficiently. These skills are crucial for ensuring customer satisfaction, minimizing downtime, and maintaining the reputation of the payment services provider.

What is the difference between Weekend First Data Merchant Services vs Weekend Credit Card Processor?

AspectWeekend First Data Merchant ServicesWeekend Credit Card Processor
CredentialsTypically requires merchant account setup knowledge, basic sales certificationsRequires understanding of credit card processing, compliance, and security standards
Work EnvironmentCustomer service, sales, and technical support in retail or online settingsTechnical support, sales, and account management in financial services
Industry UsageUsed by merchants to accept card payments, often via First Data systemsUsed by businesses to process credit card transactions through various providers

Weekend First Data Merchant Services focuses on providing merchant account solutions and support for accepting card payments, often through First Data systems. Weekend Credit Card Processor refers to professionals managing credit card transaction processing for businesses. While both roles involve payment processing, the former emphasizes merchant services, and the latter centers on transaction management. Understanding these differences helps businesses choose the right service provider or career path.

What is a weekend First Data Merchant Services representative?

Weekend First Data Merchant Services jobs typically involve working for First Data, a payment processing and financial technology company, during weekends. Employees in these roles may assist merchants with payment solutions, troubleshoot transaction issues, provide customer support, and ensure secure processing of credit card payments. The work can include both technical and customer service responsibilities, depending on the specific position. Weekend shifts are often needed to ensure merchants receive support outside of standard business hours.

What are the typical responsibilities and challenges faced by someone working weekend shifts at First Data Merchant Services?

Working weekend shifts at First Data Merchant Services often involves providing customer support to merchants, resolving payment processing issues, and monitoring transaction activity for fraud. One common challenge is managing higher call volumes or urgent issues that may arise outside standard business hours, requiring quick problem-solving and clear communication. Additionally, weekend team members may collaborate remotely with colleagues or escalate complex cases to weekday teams, so strong organizational skills and adaptability are essential in this environment.
What cities in California are hiring for Weekend First Data Merchant Services jobs? Cities in California with the most Weekend First Data Merchant Services job openings:

Senior Data Scientist

Nash

San Francisco, CA • On-site

$180 - $240/hr

Other

Medical, Dental, Vision, PTO

Posted 8 days ago


Job description

Senior Data ScientistAbout Nash

Nash is the autonomic logistics platform. We unify decisioning and execution across fleets, carriers, providers, and fulfillment networks, continuously adapting as conditions change and pursuing the best possible outcome for each business.

The world’s largest retailers, grocers, and pharmacies, including Walmart, 7-Eleven, Woolworths, and Coles, run critical logistics workflows on Nash. Your work will influence real-world decisions across millions of deliveries.

Nash was founded in 2021 by Mahmoud Ghulman and Aziz Alghunaim. We are backed by Y Combinator, a16z, OpenAI, and other leading investors, and headquartered in San Francisco.

About the role

We are hiring Nash’s first Data Scientist. You will combine product judgment, logistics or marketplace expertise, and pragmatic machine learning skills to build data products from discovery through production and measurement.

You will work across pricing, dispatch, carrier selection, ETA prediction, routing, and supply-demand forecasting. This is a high-ownership role for someone who can find valuable problems, turn ambiguity into measurable outcomes, and build the models and systems needed to improve those outcomes in production.

You will partner directly with Product, Engineering, Operations, customers, and company leadership.

What you’ll do
  • Identify and scope high-impact opportunities across pricing, cost prediction, dispatch, carrier selection, ETA prediction, routing, and marketplace balancing.

  • Own data science initiatives from 0→1 discovery through 1→10 iteration, deployment, and performance improvement.

  • Work with large, messy operational datasets, including delivery events, geospatial data, carrier performance, customer constraints, and SLA outcomes.

  • Build models that account for real-world logistics constraints, shifting demand, provider availability, and service requirements.

  • Develop production data pipelines and model integrations using Python, SQL, and Snowflake.

  • Partner with engineers to serve models through APIs, batch pipelines, or real-time decision systems.

  • Establish evaluation frameworks, monitoring, experimentation, and A/B testing practices.

  • Measure model performance against business outcomes such as cost, reliability, on-time delivery, and operational intervention.

  • Work directly with enterprise customers to understand their operations and convert business requirements into technical approaches.

  • Communicate findings, tradeoffs, and recommendations clearly to technical and non-technical audiences.

What you’ll bring
  • 4+ years of experience as a Data Scientist, Machine Learning Engineer, or in a related quantitative role.

  • Experience in logistics, marketplaces, supply chain, operations research, or another domain with complex real-world constraints.

  • A record of independently taking data science projects from problem definition through production and measurement.

  • Strong proficiency in Python and SQL, with experience working in cloud data warehouses. Snowflake experience is preferred.

  • Experience building and maintaining production machine learning systems. Deep MLOps specialization is not required.

  • Strong product judgment and the ability to connect modeling decisions to customer and business outcomes.

  • Comfort working with incomplete data, ambiguous questions, and changing operational conditions.

  • Clear written and verbal communication, including experience working with customers or senior stakeholders.

  • High agency in a fast-moving environment. You notice valuable problems and act on them.

Bonus
  • Experience with routing, ETA modeling, optimization algorithms, or geospatial data.

  • Familiarity with dispatch systems, carrier networks, logistics marketplaces, or pricing models.

  • Experience with supply-demand forecasting or marketplace balancing.

  • Exposure to dbt, Airflow, or related data orchestration tools.

  • Experience deploying models through APIs or real-time decision systems.

  • Prior experience at an early-stage company or in a founding data role.

Why this role matters

The decisions Nash makes affect what a delivery costs, which resource handles it, when it arrives, and whether the customer’s promise holds when conditions change.

As our first Data Scientist, you will define how Nash uses operational data to make those decisions sharper. The models you build will move quickly from analysis into live logistics workflows, giving you a direct view into their customer and business impact.

What you’ll love about Nash
  • An early-stage, well-funded company with real revenue and global enterprise customers

  • Significant ownership and autonomy, with direct collaboration with the founders

  • Quarterly team onsites to connect and align in person

  • Competitive compensation and meaningful equity

  • Flexible paid time off

  • Health, dental, and vision insurance

Equal opportunity

At Nash, we believe diverse teams are the strongest teams. We invite applicants of all genders, races, ethnicities, nationalities, ages, religions, sexual orientations, disability statuses, educational experiences, family situations, and socioeconomic backgrounds.

More about Nash

Nash is the platform that powers modern logistics.

Commerce has inverted. For decades, customers came to where products and services were. Now products and services come to them, on their terms, in real time. That shift has turned every company into a logistics company, even though almost none of them were built to be one. Couriers, fleets, gig workers, parcel carriers, in-store labor, and increasingly autonomous systems all have to be coordinated in real time, against tighter windows and rising expectations, with hard-fought customer trust on the line.

Nash unifies decisioning, execution, and capacity into a single programmable platform. Real-time, AI-native intelligence determines what should happen, operational control executes it, and the platform dynamically orchestrates capacity from any source: a company's own fleets, partners, or the Nash delivery network. Whether a job involves a courier, a gig driver, an internal fleet, a store employee, a technician, or an autonomous vehicle, Nash selects the right resource and manages execution through completion.

We power delivery and logistics for some of the most recognizable brands in commerce, including Walmart, Urban Outfitters, 7-Eleven, and Woolworths, alongside platforms like Shopify and Toast. Over the next decade, logistics will become as foundational to commerce as payments, cloud, and connectivity. Nash is the platform that powers it.

Nash was founded in 2021 by Mahmoud Ghulman (2x Founder, MIT) and Aziz Alghunaim (2x Founder, 2x YC, Ex-Palantir, MIT) and is backed by Y Combinator, a16z, and other top investors. We are headquartered in San Francisco.

What You’ll Love About Us

Early-stage, well-funded startup – directly impact the company and grow your career!
Quarterly broader team on-sites to bond with teammates
Competitive compensation and opportunity for equity
Flexible paid time off
Health, dental, and vision insurance

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