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Customer Facing Data Scientist Jobs (NOW HIRING)

Boston Region MPO / CTPS

Senior Data Scientist

Boston, MA · On-site

$85K - $100K/yr

The senior data scientist will lead the exploration of new datasets, administer public-facing data visualization applications, and coordinate with the MPO's project teams and staff on the Data ...

OpenRouter, Inc

Data Scientist

$180K - $240K/yr

You will work directly with our customer-facing and product teams to understand how requests are ... data science, applied ML, or quantitative product role at a high-growth, high-velocity company.

Northbeam

Senior Data Scientist

Translate statistical and causal inference methodologies into scalable, reliable customer-facing ... Partner closely with teammates across Data Science, Engineering, Product, and Customer Success to ...

Anomali Inc.

Senior Data Scientist

Redwood City, CA · On-site

... customer facing data products, visualizations, and analytics. You will apply advanced machine ... Has presented at a security, data science, or big data conference. * Prior experience working in ...

RELX

Data Scientist

Are you looking for a Client Facing Data Scientist role to help drive innovation in the fraud ... About the Business LexisNexis Risk Solutions provides customers with innovative technologies ...

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How much do customer facing data scientist jobs pay per year?

As of Aug 19, 2026, the average yearly pay for customer facing data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is a customer facing data scientist?

A Customer Facing Data Scientist combines technical data expertise with customer interaction skills to help clients derive value from data-driven solutions. They work closely with customers to understand their business needs, develop models or analyses, and communicate insights effectively. This role often involves pre-sales support, post-sales implementation, and ongoing customer consultation, requiring both strong analytical capabilities and the ability to explain complex data concepts to non-technical audiences.

What does a customer facing data scientist do?

A typical day for a Customer Facing Data Scientist involves meeting with clients to understand their business objectives, analyzing datasets to extract actionable insights, and preparing clear, impactful presentations or reports for stakeholders. You may collaborate with sales or product teams to translate technical results into business recommendations or proposals. Additionally, there is often a need to provide technical support, answer client questions, and iterate on models based on feedback. The role is highly interactive, blending technical problem-solving with client engagement in a fast-paced, dynamic environment.

What are the key skills and qualifications needed to thrive as a customer facing data scientist?

To thrive as a Customer Facing Data Scientist, you need advanced analytical skills, a solid understanding of machine learning, statistical modeling, and a relevant degree—often in Computer Science, Mathematics, or a related field. Experience with programming languages such as Python or R, data visualization tools like Tableau, and knowledge of cloud platforms (e.g., AWS, Azure) or certifications in data science are highly valuable. Excellent communication, active listening, and the ability to translate technical findings into business insights are crucial soft skills. These qualities enable effective collaboration with clients, ensuring data-driven solutions are both technically robust and aligned with real-world business needs.

Is a customer facing data scientist job still in demand?

Customer facing data scientist roles remain in demand as companies seek professionals who can interpret data and communicate insights to clients and stakeholders. Skills in machine learning, data visualization, and tools like Python or R enhance employability in this field, which is expected to grow with increasing data-driven decision-making across industries.
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Customer Facing Data Scientist jobs near you
Infographic showing various Customer Facing Data Scientist job openings in the United States as of August 2026, with employment types broken down into 50% Full Time, and 50% Temporary. Highlights an 100% In-person job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Senior Data Engineer, Customer-Facing Data Products

The New York Times

New York, NY • Hybrid

$116K - $157K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 19 days ago

Job description

About the Role

The New York Times is looking for a Senior Data Engineer to join the Customer-Facing Data Products team to develop real-time data pipelines and APIs that process events and serve aggregated data for customer-facing use cases. You will report to the Engineering Manager for the Customer-Facing Data Products team and build widely reusable solutions to help partner teams solve our most important real-time needs, including behavioral and targeting use cases.

This is a hybrid role based in our New York City headquarters.

Responsibilities:

  • Develop real-time data pipelines using event-driven architectures and streaming technologies.
  • Ingest and organize structured and unstructured data for widespread reuse across patterns.
  • Engineer and scale high availability data serving capabilities to meet customer-facing needs.
  • Implement mechanisms to ensure data quality, observability and governance best practices.
  • Collaborate with software engineers and infrastructure teams to improve pipeline performance and integrate solutions into production environments.
  • Grow the skills of colleagues by providing clear technical feedback through pairing, design, and code review.
  • Stay current with latest technologies, keeping up with the latest advancements in streaming data processing and related technologies.
  • Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

  • 5+ years of full-time data engineering experience shipping real-time solutions with event-driven architectures and stream-processing frameworks
  • Experience with cloud native architectures (AWS preferred), including service offerings and tools
  • Understanding of modern API design principles and technologies, including REST, GraphQL, and gRPC for data serving
  • Programming fluency with Python
  • Experience using version control and CI/CD tools, such as Github Actions and Drone

Preferred Qualifications:

  • Experience developing streaming pipelines with Apache Kafka, Apache Flink, or Spark Streaming
  • Experience building APIs using Python frameworks (FastAPI, Flask)
  • Experience with SQL
  • Understanding of modern data platforms including data lakehouse and medallion architectures
  • Experience collaborating with product and partners to meet shared goals

This role will require limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

#LI-Hybrid

REQ-020049

Compensation and Benefits For This Role:

In addition to base salary, this role is also eligible for variable pay, such as an annual bonus and restricted stock. Benefits include medical, dental and vision benefits, Flexible Spending Accounts (F.S.A.s), a company-matching 401(k) plan, employee stock purchase plan, paid vacation, paid sick days, paid parental leave, tuition reimbursement and professional development programs. 

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