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ai ml research scientist

Attentive.ai

<div>
 
 About Attentive.ai
 
 
 
 Attentive.ai is transforming the field services and construction industries with our flagship AI solution - Beam AI. Our platform empowers businesses to double their bidding capacity and accelerate growth through automation and intelligent insights.
 
 
 More than
 
 1k+ businesses
 
 across the U.S. and Canada already use our products to boost sales velocity and streamline operations. We have raised
 
 $30.5M in Series B funding
 
 , accelerating our mission to make advanced AI tools accessible, practical, and impactful in the real world. We are proudly Backed by Insight Partners, Peak XV (Surge), InfoEdge, Tenacity and Vertex Ventures.
 
 
 
 Position Description
 
 
 
 As an
 
 AI/ML Research Scientist,
 
 you will be an integral part of our AI research team focused on transforming the construction industry through cutting-edge deep learning, computer vision and NLP technologies. You will contribute to the development of intelligent systems for automated construction take-off and estimation by working with unstructured data such as blueprint, drawings (including SVGs), and PDF documents.
 
 
 In this role, you will support the end-to-end lifecycle of AI-based solutions &mdash; from prototyping and experimentation to deployment in production. Your contributions will directly impact the scalability, accuracy, and efficiency of our products.
 
 
 
 Roles &amp; Responsibilities
 
 
 
 <ul>
 <li>
 Build and deploy ML models for parsing and reasoning over construction blueprint PDFs - working with image, text and vector graphics modalities
 </li>
 <li>
 Design data pipelines for training, validation, and continuous improvement.
 </li>
 <li>
 Improve model accuracy, latency, and scalability for production workloads.
 </li>
 <li>
 Contribute to system architecture decisions for ML deployment and monitoring.
 </li>
 <li>
 Collaborate with cross-functional teams including software engineers, ML researchers, and product teams
 </li>
 <li>
 Write clean, scalable, and production-ready code
 
 
 </li>
 </ul>
 
 Skills &amp; Requirements
 
 
 
 <ul>
 <li>
 3&ndash;5 years of experience in applied AI/ML and research, preferably with focus on computer vision.
 </li>
 <li>
 PhD or Master's degree in deep learning, coupled with research experience focused on image modalities.
 </li>
 <li>
 Experience working with document understanding, OCR pipelines, or structured extraction systems is a plus.
 </li>
 <li>
 Deep understanding of unsupervised learning techniques like clustering, dimensionality reduction, and representation learning.
 </li>
 <li>
 Proficiency in Python and ML frameworks such as PyTorch, OpenCV, TensorFlow, and HuggingFace Transformers.
 </li>
 <li>
 Hands-on experience with model optimization techniques (e.g., quantization, pruning, knowledge distillation)
 </li>
 <li>
 Familiarity with LLM based systems and architectures
 </li>
 <li>
 Comfortable working in a fast-moving, ownership-driven environment.
 
 
 </li>
 </ul>
 
 Why Work With Us?
 
 
 
 <ul>
 <li>
 Be part of a visionary team building a first-of-its-kind AI solution for the construction industry.
 </li>
 <li>
 Exposure to real-world AI deployment and cutting-edge research in vision and multimodal learning.
 </li>
 <li>
 Culture that encourages ownership, innovation, and growth.
 </li>
 <li>
 Opportunities for fast learning, mentorship, and career progression.
 </li>
 </ul>
</div>

AI/ML Research Scientist

Call For Referral

<div>
 
 
 Machine Learning Engineer
 
 
 
 
 Work Mode:
 
 
 Remote
 
 
 
 
 Compensation:
 
 
 $100&ndash;$120 per hour
 
 
 
 
 Work Type:
 
 
 Hourly, Independent
 
 
 
 
 Role Overview
 
 
 
 This role supports the evaluation of
 
 advanced machine learning systems
 
 in collaboration with
 
 leading AI research initiatives
 
 . It is intended for
 
 experienced machine learning engineers and researchers
 
 who can contribute to the development of
 
 high-quality evaluation suites
 
 that measure AI performance on
 
 real-world machine learning engineering tasks
 
 .
 
 
 The work focuses on translating
 
 practical ML research and engineering workflows
 
 into
 
 structured benchmarks
 
 for
 
 frontier models
 
 . This is a
 
 project-based, fully remote
 
 opportunity for professionals with
 
 strong hands-on ML research and engineering experience
 
 .
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 
 Design and develop
 
 detailed evaluation suites for machine learning engineering tasks
 </li>
 <li>
 
 Evaluate AI-generated solutions
 
 across model training, debugging, optimization, and experimentation workflows
 </li>
 <li>
 
 Analyze and document
 
 system behavior, performance characteristics, and limitations
 </li>
 <li>
 
 Contribute to the creation of benchmarks
 
 that reflect real-world ML engineering practices
 </li>
 <li>
 
 Maintain high standards
 
 of technical accuracy, clarity, and consistency in all deliverables
 </li>
 </ul>
 
 
 Qualifications
 
 
 <ul>
 <li>
 
 3+ years
 
 of experience in machine learning engineering or applied ML research
 </li>
 <li>
 
 Hands-on experience
 
 with model development, experimentation, and evaluation
 </li>
 <li>
 
 Background in ML research
 
 in an industry or academic setting (strongly preferred)
 </li>
 <li>
 
 Strong ability
 
 to reason about ML system design choices and technical trade-offs
 </li>
 <li>
 
 Excellent written communication skills
 
 and
 
 high attention to technical detail
 
 </li>
 </ul>
 
 
 Work &amp; Payment Details
 
 
 <ul>
 <li>
 You will operate as an
 
 independent professional
 
 </li>
 <li>
 This is a
 
 fully remote
 
 role with a
 
 flexible schedule
 
 </li>
 <li>
 Projects may be
 
 extended, shortened, or concluded
 
 based on needs and performance
 </li>
 <li>
 The work does
 
 not involve access to confidential or proprietary information
 
 from any employer, client, or institution
 </li>
 <li>
 
 Payments are made weekly
 
 via
 
 Stripe or Wise
 
 , based on services delivered
 </li>
 <li>
 Candidates requiring
 
 H1-B or STEM OPT
 
 sponsorship are
 
 not supported
 
 at this time
 </li>
 </ul>
 
 
 Application &amp; Onboarding Process
 
 
 <ul>
 <li>
 
 Upload your resume
 
 </li>
 <li>
 
 AI interview:
 
 A short
 
 15-minute
 
 conversational session to understand your background, experience, and interest in the role
 </li>
 <li>
 
 Follow-up communication
 
 within a few days with next steps and onboarding details
 </li>
 </ul>
 
 
</div>

Machine Learning Engineer (Remote)  $100 –$120/hr

YO IT Consulting

<div>
 
 Engagement Type:
 
 Independent Contractor
 
 
 
 Work Mode:
 
 Fully Remote
 
 
 
 Contract Type:
 
 Project-Based (Short-Term, Extendable)
 
 
 
 Role Overview
 
 
 
 collaborating with a leading AI research lab to support the evaluation of advanced machine learning systems. We are seeking experienced machine learning engineers and researchers to contribute to the design of high-quality evaluation suites that measure AI performance on real-world machine learning engineering tasks. The work focuses on translating practical ML research and engineering workflows into structured benchmarks for frontier models. This is a project-based, remote opportunity suited for experts with hands-on ML research experience.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design and write detailed evaluation suites for machine learning engineering tasks
 </li>
 <li>
 Assess AI-generated solutions across areas such as model training, debugging, optimization, and experimentation
 
 
 </li>
 </ul>
 
 Ideal Qualifications
 
 
 
 <ul>
 <li>
 3+ years of experience in machine learning engineering or applied ML research
 </li>
 <li>
 Hands-on experience with model development, experimentation, and evaluation
 </li>
 <li>
 Background in ML research (industry lab or academic setting strongly preferred)
 </li>
 <li>
 Strong ability to reason about ML system design choices and tradeoffs
 </li>
 <li>
 Clear written communication and high attention to technical detail
 
 
 </li>
 </ul>
 We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.
 
 
 Contract and Payment Terms
 
 
 <ul>
 <li>
 You will be engaged as an independent contractor.
 </li>
 <li>
 This is a fully remote role that can be completed on your own schedule.
 </li>
 <li>
 Projects can be extended, shortened, or concluded early depending on needs and performance.
 </li>
 <li>
 Your work at will not involve access to confidential or proprietary information from any employer, client, or institution.
 </li>
 <li>
 Payments are weekly on Stripe or Wise based on services rendered.
 </li>
 </ul>
</div>

Machine Learning Engineer - Remote

Uber

<div>About the Role
 
 
Have you ever wondered why it's taking so long for an earner to be matched to your trip, why the ETA is so long, or how an Earner is picked from the many around you? If so, the Mobility Matching Science team is for you!
 
 
The Matching team at Uber builds the systems that determine the optimal way to fulfill trips on the Mobility platform. We work on the problems of determining which earners to send an offer to and when. The solutions we build are critical for maintaining reliability and ensuring the trust of riders and earners alike.
 
 
We are looking for experienced scientists who relish the opportunity to develop novel approaches and apply them at Uber's scale. They ideally have a good balance of causal inference, analysis, experimentation, and modeling knowledge, as well as, an ability to use these skills to identify business opportunities and deliver product recommendations.
 
 
What You'll Do
<ul><li>Develop data-driven business insights and work with cross-functional stakeholders to identify opportunities and recommend prioritization of product, growth and optimization initiatives
</li><li>Design and analyze experiments, communicating results that draw detailed and actionable conclusions
</li><li>Analyze and contribute to development of optimization algos and ML models for use in mobility matching
</li><li>Collaborate with cross-functional teams such as product, engineering and operations to drive system development end-to-end from conceptualization to final product
</li></ul>Basic Qualifications
<ul><li>Ph.D. in Statistics, Economics, Machine Learning, Operations Research, Computer Science, or another quantitative field.
</li><li>Minimum 2 years of industry experience as an Applied Scientist, Data Scientist, or in a similar quantitative role.
</li><li>Strong knowledge of the mathematical foundations of statistics, machine learning, optimization, and economics.
</li><li>Proven experience in experimental design (e.g., A/B testing) and causal inference.
</li><li>Proficiency in using Python or R for data analysis, modeling, and algorithm prototyping at scale with large datasets.
</li><li>Experience with exploratory data analysis, statistical analysis and testing, and model development.
</li></ul>Preferred Qualifications
<ul><li>Ph.D., or M.S. in Statistics, Economics, Machine Learning, Operations Research, Computer Science, or another quantitative field.
</li><li>Minimum 5 years of industry experience as an Applied Scientist, Data Scientist, or in a similar quantitative role.
</li><li>Strong knowledge of the mathematical foundations of statistics, machine learning, optimization, and economics.
</li><li>Proven experience in experimental design (e.g., A/B testing) and causal inference.
</li><li>Proficiency in using Python or R for data analysis, modeling, and algorithm prototyping at scale with large datasets.
</li>Experience with exploratory data analysis, statistical analysis and testing, and model development. 
<li>
</li></ul> 
 
For San Francisco, CA-based roles: The base salary range for this role is USD$190,000 per year - USD$211,000 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.</div>

Sr. Scientist - Mobility Matching

Cartesia

<div><h1 class="jobSectionHeader">About Cartesia</h1>
Our mission is to build the next generation of AI: ubiquitous, interactive intelligence that runs wherever you are. Today, not even the best models can continuously process and reason over a year-long stream of audio, video and text&mdash;1B text tokens, 10B audio tokens and 1T video tokens&mdash;let alone do this on-device.
We're pioneering the model architectures that will make this possible. Our founding team met as PhDs at the Stanford AI Lab, where we invented State Space Models or SSMs, a new primitive for training efficient, large-scale foundation models. Our team combines deep expertise in model innovation and systems engineering paired with a design-minded product engineering team to build and ship cutting edge models and experiences.
We're funded by leading investors at Index Ventures and Lightspeed Venture Partners, along with Factory, Conviction, A Star, General Catalyst, SV Angel, Databricks and others. We're fortunate to have the support of many amazing advisors, and 90+ angels across many industries, including the world's foremost experts in AI.
About the Role
We're looking for an exceptional Product Manager to join Cartesia and help shape the future of voice AI. In this role, you'll drive product strategy and execution across our platform, working at the intersection of cutting-edge AI technology and real-world customer needs. You'll own the product roadmap for your area, make data-informed decisions, and collaborate closely with engineering, research, design, and go-to-market teams to build products that set the standard for voice AI.
This is a high-impact, high-ownership role at an early-stage company where your work will directly shape Cartesia's trajectory. You'll be embedded in a fast-moving team that cares deeply about quality, craft, and building products developers and enterprises love. 
Your Impact<ul><li>
Define and own the product roadmap for your area, translating company strategy into prioritized initiatives with clear goals and measurable outcomes</li><li>
Partner with engineering and research teams to scope, design, and ship high-quality product experiences&mdash; balancing speed with long-term quality</li><li>
Develop a deep understanding of Cartesia's customers, their workflows, and their pain points through direct engagement, qualitative research, and quantitative analysis</li><li>
Drive cross-functional alignment across research, data, engineering, design, and GTM teams to prioritize and execute on the highest-impact opportunities</li><li>
Define success metrics for your product area and establish a culture of measurement, using data to inform decisions and evaluate impact</li><li>
Conduct competitive analysis to identify gaps, opportunities, and differentiation strategies that position Cartesia as the leading voice AI platform</li><li>
Communicate clearly and persuasively with both technical and non-technical stakeholders, from individual engineers to executive leadership</li><li>
Build frameworks and documentation that help internal teams and customers understand product capabilities, limitations, and best practices</li></ul>
What You Bring<ul><li>
6+ years of product management experience with technical products, preferably in AI/ML, developer tools, or infrastructure</li><li>
Proven ability to define product strategy, make difficult prioritization decisions, and drive execution in a fast-paced environment</li><li>
Strong analytical mindset with experience defining success metrics, designing experiments, and making data-driven decisions</li><li>
Deep customer empathy with a track record of conducting user research, synthesizing qualitative feedback, and translating insights into impactful product requirements</li><li>
Technical fluency to collaborate effectively with ML researchers, data scientists, and engineers&mdash; able to engage deeply on implementation tradeoffs</li><li>
Excellent cross-functional collaboration and communication skills; able to build trust and influence without direct authority</li><li>
Comfort operating in ambiguity and a strong bias toward action and iterative learning</li></ul>
Nice to Have<ul><li>
Direct experience with voice AI, speech technologies (TTS, STT), or conversational AI products</li><li>
Background in developer tools, API products, or infrastructure&mdash;especially with usage-based or self-serve growth models</li><li>
Experience building from 0 1 at an early-stage startup, or founder experience</li><li>
Familiarity with ML model evaluation, A/B testing methodologies, or data pipeline design</li><li>
SQL proficiency or experience with analytics tools such as Amplitude, Mixpanel, or Looker</li></ul> 
What We Offer
Lunch, dinner and snacks at the office
Fully covered medical, dental, and vision insurance for employees
401(k)
Relocation and immigration support
Your own personal Yoshi<h2 class="jobSectionHeader">
Our Culture</h2>
We&rsquo;re an in-person team based out of San Francisco. We love being in the office, hanging out together, and learning from each other every day.
We ship fast. All of our work is novel and cutting edge, and execution speed is paramount. We have a high bar, and we don&rsquo;t sacrifice quality or design along the way.
We support each other. We have an open &amp; inclusive culture that&rsquo;s focused on giving everyone the resources they need to succeed.
Compensation Range: $200K - $270K</div>

Product Manager

OpenAI

<div>
 
 About The Team
 
 
 
 OpenAI&rsquo;s mission is to build safe artificial general intelligence (AGI) that benefits all of humanity. Achieving this requires bringing the world&rsquo;s most exceptional talent under one roof to push the boundaries of what&rsquo;s possible.
 
 
 Our Research Recruiting team plays a critical role in this effort. We are an embedded part of the research organization, working side by side with our research staff to deeply understand evolving priorities, build trust, and strategically shape the future of OpenAI&rsquo;s talent.
 
 
 
 About The Role
 
 
 
 You will own and execute long-term talent strategies to identify, engage, and recruit many of the world&rsquo;s leading and emerging AI researchers, research engineers, and technical scientists working at the frontier of machine learning. This is not a traditional execution-focused recruiting role.
 
 
 You will operate as a strategic partner to OpenAI&rsquo;s research staff, helping define hiring priorities, shape search strategy, influence candidate evaluation, and guide hiring decisions that directly impact the direction and quality of our frontier-model research and fulfillment of our mission.
 
 
 
 In This Role, You Will
 
 
 
 <ul>
 <li>
 Partner directly with research and technical staff to define hiring priorities, shape search strategies, and anticipate future talent needs as technical roadmaps evolve.
 </li>
 <li>
 Proactively identify and cultivate exceptional AI/ML research talent across industry, academia, and emerging labs, often before formal hiring needs exist.
 </li>
 <li>
 Use market insights and candidate signals to influence hiring decisions, leveling, and compensation strategy for highly specialized research roles.
 </li>
 <li>
 Serve as a trusted advisor throughout candidate evaluation and closing &mdash; helping leaders calibrate for research excellence, long-term potential, and organizational fit.
 </li>
 <li>
 Collaborate closely with your sourcing partner to execute complex, high-impact searches in ambiguous or rapidly evolving technical domains.
 
 
 </li>
 </ul>
 
 You Might Thrive In This Role If You
 
 
 
 <ul>
 <li>
 Significant experience recruiting within highly technical or specialized environments.
 </li>
 <li>
 Deep interest in AI research and a desire to engage directly with global research communities.
 </li>
 <li>
 Experience recruiting within highly technical or specialized environments such as ML/AI, distributed systems, infrastructure, scientific computing, or quantitative research.
 </li>
 <li>
 Track record of leading complex, ambiguous technical searches from early talent mapping through close.
 </li>
 <li>
 Experience navigating high-stakes negotiations with senior technical or research candidates.
 </li>
 <li>
 Comfort operating in fast-moving environments where hiring priorities and role definitions may evolve over time.
 
 
 </li>
 </ul>
 
 Workplace &amp; Location
 
 
 
 This role is based in our San Francisco office and we aren&rsquo;t considering remote applications at this time. We use a hybrid work model of 3 days in the office with optional work from home on Thursdays and Fridays. We also offer relocation assistance to new employees.
 
 
 Our open-plan offices have height-adjustable desks, conference rooms, phone booths, well-stocked kitchens full of snacks and drinks, three in-house prepared meals daily, outdoor space for working and socializing, wellness rooms, private bike storage, and more.
 
 
 
 About OpenAI
 
 
 
 OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
 
 
 We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
 
 
 For additional information, please see OpenAI&rsquo;s Affirmative Action and Equal Employment Opportunity Policy Statement.
 
 
 Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
 
 
 To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
 
 
 We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
 
 
 OpenAI Global Applicant Privacy Policy
 
 
 At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
 
 
 Compensation Range: $216K - $240K
</div>

Recruiter, AI/ML Research

Intercom

<div><div>Intercom is the AI Customer Service company on a mission to help businesses provide incredible customer experiences.

Our AI agent Fin, the most advanced customer service AI agent on the market, lets businesses deliver always-on, impeccable customer service and ultimately transform their customer experiences for the better. Fin can also be combined with our Helpdesk to become a complete solution called the Intercom Customer Service Suite, which provides AI enhanced support for the more complex or high touch queries that require a human agent.

Founded in 2011 and trusted by nearly 30,000 global businesses, Intercom is setting the new standard for customer service. Driven by our core values, we push boundaries, build with speed and intensity, and consistently deliver incredible value to our customers.</div><div><h2 class="jobSectionHeader">
What's the opportunity?</h2>

Intercom is building a GTM Data Products team to embed machine learning and AI directly into our Sales and Marketing workflows.

We are hiring a Senior GTM Data Scientist to design and deploy predictive systems that materially improve:
<ul>
<li>Customer acquisition (e.g. via lead scoring, attribution)</li>
<li>Sales efficiency (e.g. via book carves, sales quotas)</li>
<li>Customer retention and expansion (e.g. via revenue prediction)</li>
</ul>
This is not a reporting role.

This role owns end-to-end data products - from problem framing and modeling to deployment and operational integration - that directly influence how our GTM organization prioritizes leads, manages accounts, allocates resources, and drives revenue.

You&rsquo;ll work closely with Marketing, Sales, and RevOps leadership to build ML-powered systems that change how decisions are made at scale.

If you are excited about building applied machine learning systems that generate measurable revenue impact, this role is for you.
<h2 class="jobSectionHeader">
What will I be doing?</h2>
<div><ul><li>Build Revenue-Impacting ML Systems</li></ul>
</div><ul><li>Develop, deploy, optimize predictive models (lead scoring, account prioritization, marketing attribution, revenue estimation)</li>
<li>Productionize models into operational systems (Salesforce, Marketo, outbound workflows)</li>
<li>Monitor model performance and iterate for measurable business lift</li>
<li>Design and implement experimentation frameworks (A/B testing, holdouts, incremental lift measurement)</li>
<li>Apply advanced techniques when appropriate (e.g., causal inference, uplift modeling, segmentation, LTV modeling)</li>
</ul>
You don&rsquo;t just build models - you ensure they change behavior.
<div>
<ul><li>Own End-to-End Data Products</li></ul>
</div><ul><li>Translate ambiguous business problems into clear, measurable objectives</li>
<li>Define GTM data products vision, success metrics, and roadmap</li>
<li>Ensure integration into existing workflows and systems</li>
<li>Lead stakeholder alignment and change management</li>
<li>Secure buy-in from system owners before replacing or enhancing existing solutions</li>
</ul>
You operate as a mini GM for your data products.

 3. Architect Scalable Data Foundations
<ul>
<li>Design robust data pipelines and modeling infrastructure in collaboration with Data Engineering / Data Infrastructure</li>
<li>Ensure data quality, governance, and reproducibility</li>
<li>Elevate the team&rsquo;s standards for experimentation, documentation, and knowledge sharing</li>
<li>Push adoption of new tools and AI capabilities where appropriate</li>
</ul>
You raise the technical bar for the GTM organization.
<h2 class="jobSectionHeader">
What impact might I have?</h2>

Within 6-12 months, you might:
<ul>
<li>Launch predictive models that materially improve conversion, expansion, or retention</li>
<li>Reduce inefficiencies in Sales workflows through automation</li>
<li>Help leadership make investment decisions backed by rigorous data science</li>
<li>Influence GTM strategy through quantitative insight and modeling</li>
</ul>
Success is measured in business outcomes - not dashboards built.
<h2 class="jobSectionHeader">
What we&rsquo;re looking for</h2>

Experience
<ul>
<li>5+ years in Data Science, Applied ML, or Advanced Analytics</li>
<li>Experience building predictive models deployed into production environments</li>
<li>Experience working with Sales, Marketing, or GTM teams in a B2B SaaS environment preferred</li>
<li>Proven track record influencing senior stakeholders through data</li>
</ul>
Technical Skills
<ul>
<li>Expert-level SQL</li>
<li>Advanced Python or R for modeling and experimentation</li>
<li>Strong foundation in statistics and experimental design</li>
<li>Experience with:</li>
<li><ul><li>Predictive modeling</li>
<li>Feature engineering</li>
<li>Model evaluation &amp; validation</li>
<li>Causal inference or uplift modeling (strong plus)</li>
<li>Model deployment &amp; monitoring (strong plus)</li>
</ul></li>
</ul>Mindset &amp; Leadership

You are:
<ul>
<li>A trusted advisor who influences strategy, not just execution</li>
<li>Deeply curious about the &ldquo;why&rdquo; behind business metrics</li>
<li>Comfortable operating with autonomy in ambiguous environments</li>
<li>AI-first: you look for opportunities to automate, optimize, and scale</li>
<li>Clear and compelling in communication - you turn complex models into strategic decisions</li>
<li>Impact-oriented: you prioritize work that moves revenue</li>
</ul><h2 class="jobSectionHeader">Benefits</h2>

We are a well-treated bunch with awesome benefits! If there&rsquo;s something important to you that&rsquo;s not on this list, talk to us! :)
<ul>
<li>Competitive salary and meaningful equity</li>
<li>Comprehensive medical, dental, and vision coverage</li>
<li>Regular compensation reviews - great work is rewarded!</li>
<li>Flexible paid time off policy</li>
<li>Paid Parental Leave Program</li>
<li>401k plan &amp; match</li>
<li>In-office bicycle storage</li>
<li>Fun events for Intercomrades, friends, and family!</li>
</ul>
<ul><li>Proof of eligibility to work in the United States is required</li></ul>

The base salary range for candidates within the San Francisco Bay Area is $197,600 - $246,713. Actual base pay will depend on a variety of factors such as education, skills, experience, location, etc. The base pay range is subject to change and may be modified in the future. All regular employees may also be eligible for the corporate bonus program or a sales incentive (target included in OTE) as well as stock in the form of Restricted Stock Units (RSUs).
#LI-Hybrid</div><div>
Policies

Intercom has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week.

We have a radically open and accepting culture at Intercom. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values.
Intercom values diversity and is committed to a policy of Equal Employment Opportunity. Intercom will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other legally recognized protected basis under federal, state, or local law.</div></div>

Senior GTM Data Scientist New

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