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Customer Facing Data Scientist Jobs (NOW HIRING)

OpenRouter, Inc

$100 - $140/hr

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.

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.

Plat.AI

Front-Facing Data Analyst

Glendale, CA · On-site

We are seeking a highly analytical and business-savvy Front-Facing Data Analyst to serve as the bridge between our data science team and external stakeholders. This role combines strong technical ...

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 ...

Compunnel

Data Scientist

Raleigh, NC · On-site

We are seeking a Senior Data Scientist to lead the design and validation of AI-driven product ... scalable, customer-facing solutions. Key Responsibilities: • Lead experimentation and model ...

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

As of Aug 26, 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 Scientist[Remote]- W2 Role

Raleigh, NC • On-site

SmartIPlace
IT Services • 51 - 200 employees
Learn more about SmartIPlaceexternal

Contractor

Posted 8 days ago

Job description

Senior Data Scientist II
Position: Senior Data Scientist II
Location: Remote (EST) — Hybrid in Raleigh, NC preferred
Rate Type: BH W2
Duration: 6 months, with possible extension/conversion
Interview Process: 2 rounds via video

Position Overview

LexisNexis is seeking experienced Senior Data Scientist II professionals to develop innovative, customer-facing data science and AI solutions. The ideal candidate will have strong expertise in modern data science, Generative AI, LLMs, RAG, agentic AI, unstructured data, and production machine learning.

You will work closely with Machine Learning Engineers (MLEs) and cross-functional teams throughout the product development and production lifecycle, turning complex data into scalable, customer-focused solutions.

Required Qualifications

  • 8+ years of total professional experience in data science, machine learning, or a closely related field.
  • 5+ years of recent Data Science experience, with hands-on expertise in areas such as:
    • MCP
    • RAG implementations, evaluations, validations, and proof-of-concepts
    • Agentic AI
    • Generative AI
    • LLM applications
    • Unstructured data
  • Proven experience building customer-facing data science or AI products.
  • Experience partnering with Machine Learning Engineers (MLEs) throughout the production lifecycle.
  • Strong Python programming skills.
  • Strong understanding of machine learning algorithms, including:
    • Deep Learning
    • Gradient Boosting
    • Random Forests
  • Experience working directly with Large Language Models (LLMs) and Transformer-based architectures, including:
    • BERT
    • RoBERTa
    • T5
  • Hands-on experience applying LLM technologies such as:
    • ChatGPT
    • GPT-3.5
    • Claude
    • Mistral
  • Experience working with large datasets and distributed computing systems, such as Hadoop and Spark.

Preferred Qualifications

  • Experience working within large enterprise environments.
  • Experience taking AI/ML solutions from experimentation and proof-of-concept through production.
  • Strong understanding of modern Generative AI and LLM ecosystem.
  • Experience working with cross-functional teams to deliver business and customer-focused solutions.

Key Responsibilities

  • Develop advanced data science and AI solutions using complex datasets.
  • Design, implement, evaluate, and validate RAG, agentic AI, MCP, and Generative AI solutions.
  • Work with unstructured data to extract meaningful insights and develop innovative AI applications.
  • Apply machine learning and deep learning techniques to solve complex business problems.
  • Work directly with LLMs and Transformer-based architectures.
  • Collaborate closely with MLEs to move models and AI solutions into production.
  • Contribute to the full product lifecycle, from research and experimentation through deployment and optimization.
  • Analyze large-scale datasets using distributed computing technologies such as Spark and Hadoop.
  • Partner with cross-functional teams to translate business requirements into data-driven solutions.
  • Drive actionable insights that support business strategy, customer experience, and product growth.
  • Stay current with emerging developments in Generative AI, LLMs, machine learning, and AI engineering.

Ideal Candidate

The ideal candidate is a senior-level Data Scientist with strong hands-on Generative AI/LLM experience, particularly someone who has recently worked on RAG, MCP, agentic AI, unstructured data, and customer-facing AI products and has experience taking solutions into production.

Must-Have Keywords:
Python | Data Science | Generative AI | LLM | RAG | MCP | Agentic AI | Unstructured Data | Machine Learning | Deep Learning | Transformers | BERT | RoBERTa | T5 | Spark | Hadoop | Customer-Facing Products | MLE Collaboration

Smart-iPlace logo

About Smart-iPlace

Sourced by ZipRecruiter

SMART-iPLACE provides innovative staffing and consulting solutions that help our clients achieve their business objectives. We can understand and support all areas of your IT systems from back-end infrastructure to front-end personal productivity. Our goal is create innovative IT solutions that enable your business to be more agile and competitive.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Irving, TX, US

Year founded

2021

Social media

Facebook

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