Senior data scientist jobs in San Jose, CA

Salary: $200-250k base + RSUs This fast-growing Series E AI SaaS company is redefining how modern engineering teams build and deploy applications. We're looking for a Staff Data Scientist to drive Sales and Go-to-Market (GTM) analytics, applying advanced modeling and experimentation to accelerate revenue growth and optimize the full sales funnel. About the Role As the senior data scientist supporting Sales and GTM, you will combine statistical modeling, experimentation, and advanced analytics to inform strategy and guide decision-making across our revenue organization. Your work will help leadership understand pipeline health, predict outcomes, and identify the levers that unlock sustainable growth. Key Responsibilities Model the Business: Build forecasting and propensity models for pipeline generation, conversion rates, and revenue projections. Optimize the Sales Funnel: Analyze lead scoring, opportunity progression, and deal velocity to recommend improvements in acquisition, qualification, and close rates. Experimentation & Causal Analysis: Design and evaluate experiments (A/B tests, uplift modeling) to measure the impact of pricing, incentives, and campaign initiatives. Advanced Analytics for GTM: Apply machine learning and statistical techniques to segment accounts, predict churn/expansion, and identify high-value prospects. Cross-Functional Partnership: Work closely with Sales, Marketing, RevOps, and Product to influence GTM strategy and ensure data-driven decisions. Data Infrastructure Collaboration: Partner with Analytics Engineering to define data requirements, ensure data quality, and enable self-serve reporting. Strategic Insights: Present findings to executive leadership, translating complex analyses into actionable recommendations. About You Experience: 6+ years in data science or advanced analytics roles, with significant time spent in B2B SaaS or developer tools environments. Technical Depth: Expert in SQL and proficient in Python or R for statistical modeling, forecasting, and machine learning. Domain Knowledge: Strong understanding of sales analytics, revenue operations, and product-led growth (PLG) motions. Analytical Rigor: Skilled in experimentation design, causal inference, and building predictive models that influence GTM strategy. Communication: Exceptional ability to tell a clear story with data and influence senior stakeholders across technical and business teams. Business Impact: Proven record of driving measurable improvements in pipeline efficiency, conversion rates, or revenue outcomes.

Staff Data Scientist | San Francisco | $250K-$300K + Equity We're partnering with one of the fastest-growing AI companies in the world to hire a Staff Data Scientist. Backed by over $230M from top-tier investors and already valued at over $1B, they've secured customers that include some of the most recognizable names in tech. Their AI platform powers millions of daily interactions and is quickly becoming the enterprise standard for conversational AI. In this role, you'll bring rigorous analytics and experimentation leadership that directly shapes product strategy and company performance. What you'll do: Drive deep-dive analyses on user behavior, product performance, and growth drivers Design and interpret A/B tests to measure product impact at scale Build scalable data models, pipelines, and dashboards for company-wide use Partner with Product and Engineering to embed experimentation best practices Evaluate ML models, ensuring business relevance, performance, and trade-off clarity What we're looking for: 5+ years in data science or product analytics at scale (consumer or marketplace preferred) Advanced SQL and Python skills, with strong foundations in statistics and experimental design Proven record of designing, running, and analyzing large-scale experiments Ability to analyze and reason about ML models (classification, recommendation, LLMs) Strong communicator with a track record of influencing cross-functional teams If you're excited by the sound of this challenge- apply today and we'll be in touch.

Net2Source is a Global Workforce Solutions Company headquartered at NJ, USA with its branch offices in Asia Pacific Region. We are one of the fastest growing IT Consulting company across the USA and we are hiring " Senior Data Scientist " for one of our clients. We offer a wide gamut of consulting solutions customized to our 450+ clients ranging from Fortune 500/1000 to Start-ups across various verticals like Technology, Financial Services, Healthcare, Life Sciences, Oil & Gas, Energy, Retail, Telecom, Utilities, Technology, Manufacturing, the Internet, and Engineering. Position: Senior Data Scientist Location: Pleasanton, CA (Onsite) - Locals Only Type: Contract Exp Level - 10+ Years Required Skills Design, develop, and deploy advanced marketing models, including: Build and productionize NLP solutions. Partner with Marketing and Business stakeholders to translate business objectives into data science solutions. Work with large-scale structured and unstructured datasets using SQL, Python, and distributed systems. Evaluate and implement state-of-the-art ML/NLP techniques to improve model performance and business impact. Communicate insights, results, and recommendations clearly to both technical and non-technical audiences. Required Qualifications 5+ years of experience in data science or applied machine learning, with a strong focus on marketing analytics. Hands-on experience building predictive marketing models (e.g., segmentation, attribution, personalization). Strong expertise in NLP techniques and libraries (e.g., spa Cy, NLTK, Hugging Face, Gensim). Proficiency in Python, SQL, and common data science libraries (pandas, NumPy, scikit-learn). Solid understanding of statistics, machine learning algorithms, and model evaluation. Experience deploying models into production environments. Strong communication and stakeholder management skills. Why Work With Us? We believe in more than just jobs-we build careers. At Net2Source, we champion leadership at all levels, celebrate diverse perspectives, and empower you to make an impact. Think work-life balance, professional growth, and a collaborative culture where your ideas matter. Our Commitment to Inclusion & Equity Net2Source is an equal opportunity employer, dedicated to fostering a workplace where diverse talents and perspectives are valued. We make all employment decisions based on merit, ensuring a culture of respect, fairness, and opportunity for all, regardless of age, gender, ethnicity, disability, or other protected characteristics. Awards & Recognition America's Most Honored Businesses (Top 10%) Fastest-Growing Staffing Firm by Staffing Industry Analysts INC 5000 List for Eight Consecutive Years Top 100 by Dallas Business Journal Spirit of Alliance Award by Agile1 Maddhuker Singh Sr Account & Delivery Manager ***********************

Lead Data Scientist - Computer Vision/Image Processing About the Role We are seeking a Lead Data Scientist to drive the strategy and execution of data science initiatives, with a particular focus on computer vision systems & image processing techniques. The ideal candidate has deep expertise in image processing techniques including Filtering, Binary Morphology, Perspective/Affine Transformation, Edge Detection. Responsibilities Solid knowledge of computer vision programs and image processing techniques: Filtering, Binary Morphology, Perspective/Affine Transformation, Edge Detection Strong understanding of machine learning: Regression, Supervised and Unsupervised Learning Proficiency in Python and libraries such as OpenCV, NumPy, scikit-learn, TensorFlow/PyTorch. Familiarity with version control (Git) and collaborative development practices

Job Title: Data Scientist V - Data Analytics & Engineering Location: Onsite preferred (Mountain View, CA); Remote considered for strong candidates (US time zones only) Duration: 12 months (possible extension) Required Skills: Strong project or product management experience Excellent communication and consulting skills Proficiency in SQL and Python Nice to Have: Experience with marketing analytics or campaigns Experience in large tech or fast-paced startup environments Familiarity with AI-driven workflows Why Join: High-visibility, cross-functional role Opportunity to work on advanced measurement and automation tools Small, agile team with enterprise-scale impact

We're working with a Series A health tech start-up pioneering a revolutionary approach to healthcare AI, developing neurosymbolic systems that combine statistical learning with structured medical knowledge. Their technology is being adopted by leading health systems and insurers to enhance patient outcomes through advanced predictive analytics. We're seeking Machine Learning Engineers who excel at the intersection of data science, modeling, and software engineering. You'll design and implement models that extract insights from longitudinal healthcare data, balancing analytical rigor, interpretability, and scalability. This role offers a unique opportunity to tackle foundational modeling challenges in healthcare, where your contributions will directly influence clinical, actuarial, and policy decisions. Key Responsibilities Develop predictive models to forecast disease progression, healthcare utilization, and costs using temporal clinical data (claims, EHR, laboratory results, pharmacy records) Design interpretable and explainable ML solutions that earn the trust of clinicians, actuaries, and healthcare decision-makers Research and prototype innovative approaches leveraging both classical and modern machine learning techniques Build robust, scalable ML pipelines for training, validation, and deployment in distributed computing environments Collaborate cross-functionally with data engineers, clinicians, and product teams to ensure models address real-world healthcare needs Communicate findings and methodologies effectively through visualizations, documentation, and technical presentations Required Qualifications Strong foundation in statistical modeling, machine learning, or data science, with preference for experience in temporal or longitudinal data analysis Proficiency in Python and ML frameworks (PyTorch, JAX, NumPyro, PyMC, etc.) Proven track record of transitioning models from research prototypes to production systems Experience with probabilistic methods, survival analysis, or Bayesian inference (highly valued) Bonus Qualifications Experience working with clinical data and healthcare terminologies (ICD, CPT, SNOMED CT, LOINC) Background in actuarial modeling, claims forecasting, or risk adjustment methodologies

Key Responsibilities Design and develop marketing-focused machine learning models, including: Customer segmentation Propensity, churn, and lifetime value (LTV) models Campaign response and uplift models Attribution and marketing mix models (MMM) Build and deploy NLP solutions for: Customer sentiment analysis Text classification and topic modeling Social media, reviews, chat, and voice-of-customer analytics Apply advanced statistical and ML techniques to solve real-world business problems. Work with structured and unstructured data from multiple marketing channels (digital, CRM, social, email, web). Translate business objectives into analytical frameworks and actionable insights. Partner with stakeholders to define KPIs, success metrics, and experimentation strategies (A/B testing). Optimize and productionize models using MLOps best practices. Mentor junior data scientists and provide technical leadership. Communicate complex findings clearly to technical and non-technical audiences. Required Skills & Qualifications 7+ years of experience in Data Science, with a strong focus on marketing analytics. Strong expertise in Machine Learning (supervised & unsupervised techniques). Hands-on experience with NLP techniques, including: Text preprocessing and feature extraction Word embeddings (Word2Vec, GloVe, Transformers) Large Language Models (LLMs) is a plus Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch). Experience with SQL and large-scale data processing. Strong understanding of statistics, probability, and experimental design. Experience working with cloud platforms (AWS, Azure, or GCP). Ability to translate data insights into business impact. Nice to Have Experience with marketing automation or CRM platforms. Knowledge of MLOps, model monitoring, and deployment pipelines. Familiarity with GenAI/LLM-based NLP use cases for marketing. Prior experience in consumer, e-commerce, or digital marketing domains. EEO Centraprise is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.

About Company, Droisys is an innovation technology company focused on helping companies accelerate their digital initiatives from strategy and planning through execution. We leverage deep technical expertise, Agile methodologies, and data-driven intelligence to modernize systems of engagement and simplify human/tech interaction. Amazing things happen when we work in environments where everyone feels a true sense of belonging and when candidates have the requisite skills and opportunities to succeed. At Droisys, we invest in our talent and support career growth, and we are always on the lookout for amazing talent who can contribute to our growth by delivering top results for our clients. Join us to challenge yourself and accomplish work that matters. Here's the job details, Data Scientist with Gen Ai and Python experience Palo Alto CA- 5 days Onsite Interview Mode:-Phone & F2F Job Overview: Competent Data Scientist, who is independent, results driven and is capable of taking business requirements and building out the technologies to generate statistically sound analysis and production grade ML models DS skills with GenAI and LLM Knowledge, Expertise in Python/Spark and their related libraries and frameworks. Experience in building training ML pipelines and efforts involved in ML Model deployment. Experience in other ML concepts - Real time distributed model inferencing pipeline, Champion/Challenger framework, A/B Testing, Model. Familiar with DS/ML Production implementation. Excellent problem-solving skills, with attention to detail, focus on quality and timely delivery of assigned tasks. Azure cloud and Databricks prior knowledge will be a big plus. Droisys is an equal opportunity employer. We do not discriminate based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. Droisys believes in diversity, inclusion, and belonging, and we are committed to fostering a diverse work environment.

Title: Snowflake Data Architect - Onsite all 5 days Note: The candidate is required to attend the final interview in person at Santa Clara, CA 95054 Key Requirements: Strong hands-on experience in data engineering using Snowflake with proven ability to build and optimize large-scale data pipelines. Deep understanding of data architecture principles, including ingestion, transformation, storage, and access control. Solid experience in system design and solution architecture, focusing on scalability, reliability, and maintainability. Expertise in ETL/ELT pipeline design, including data extraction, transformation, validation, and load processes. In-depth knowledge of data modeling techniques (dimensional modeling, star, and snowflake schemas). Skilled in optimizing compute and storage costs across Snowflake environments. Strong proficiency in administration, including database design, schema management, user roles, permissions, and access control policies. Hands-on experience implementing data lineage, quality, and monitoring frameworks. Advanced proficiency in SQL for data processing, transformation, and automation. Experience with reporting and visualization tools such as Power BI and Sigma Computing. Excellent communication and collaboration skills, with the ability to work independently and drive technical initiatives.

Our Cybersecurity Startup building the next generation of products using cutting-edge technology and AI. (We are a 5-days a week in-office company located in N. San Jose, CA. Sorry, no remote hiring for this particular role) Join us at our cutting-edge AI startup in the San Francisco Bay Area, where we are assembling a world-class team to tackle some of the most pressing challenges in cybersecurity. As a Data Engineer, you will be working on components that are extremely mission-critical and form the heart of the ecosystem being built. You Have Experience In... Data engineering and data modeling Building data lakes and extracting data from diverse sources in multiple formats Designing and executing ETL processes Data warehousing and analytics More about you... 10+ years of software engineering experience, including 7+ years as a Data Engineer Proven experience building data lakes and extracting diverse data efficiently for downstream use Strong data engineering and data modeling skills Expertise in ETL, data warehousing, and data analytics Deep expertise in one or more data stores (SQL, NoSQL, with production experience in large GraphDB deployments Hands-on experience with big data technologies such as Spark and DeltaLake Cloud experience (AWS / Azure / GCP), Azure preferred Skilled in developing scalable APIs and containerizing them using Docker and Kubernetes Proficiency in Python and SQL; experience with Go or a similar language (Java, C++) Familiarity with Terraform and Infrastructure as Code (nice to have) General networking knowledge: TCP/IP, HTTP, REST Ability to work cross-functionally, including collaboration with AI teams, in a fast-paced environment with evolving requirements Bachelor's or Master's degree in Computer Science, Data Science, or a related field Why Join Us: $25M Seed Funding: We are well-funded, with $25 million raised in our seed round, giving us the resources to innovate and scale rapidly. Proven Early Success: We've already partnered with Fortune 500 companies, demonstrating market traction and trust in our AI-driven cybersecurity solutions. Experienced Leadership: Our founders are second- and third-time entrepreneurs with 25+ years in cybersecurity - having led companies to valuations exceeding $3B. World-Class Leadership Team: Heads of AI, Engineering, and Product come from top global tech companies, ensuring best-in-class mentorship and technical direction. Cutting-Edge AI Solutions: We leverage the most advanced AI technologies, including Large Language Models (LLMs), Generative AI, and intelligent inference systems. Competitive Compensation: Competitive salary, meaningful equity, and a high-growth environment where your impact is recognized and rewarded. Cybersecurity Knowledge Preferred but Not Required: We value strong AI/ML and infrastructure engineering talent above all - cybersecurity expertise can be learned on the job.

The Company: A data services company based in the heart of San Francisco, are looking for a Senior Data Engineer. They are a team of passionate engineers and data experts that are working on a variety of different project, primarily in the financial services sector, helping organizations build scalable, modern data platforms. This is a hands-on, full-time role with close collaboration alongside the CTO and senior engineers, offering strong influence over technical direction and delivery. The Role: This is an on-site position in the downtown San Francisco where you will be working as part of a close-knit team, collaborating on projects in their brand new office. You will be working across end-to-end data projects, including: Building and maintaining data pipelines and ETL processes. Sourcing and integrating third-party APIs and datasets. Batch and near-real-time processing (cloud agnostic). Downstream analytics and reporting using tools like Sigma Computing and Omnium Analytics. Collaborating with the CTO and engineering team to deliver client solutions. Key Skills: 5+ years' data engineering experience Strong Python, BigQuery, and cloud (GCP or similar) Solid ETL and pipeline background Comfortable with large-scale data Nice to Have Beam, Dataflow, Spark, or Hadoop Tableau or Looker ML/AI exposure Kafka or Pub/Sub Given the varied nature of the work, a broad range of technology experience is valued. You don't need to have experience with every tool listed below to be considered, so we encourage you to apply. This role is 5 days a week on-site in downtown San Francisco. Looking to pay between $170,000-$220,000 with a bonus between 15-20%. Benefits Health, Dental & Vision covered Unlimited PTO 401(k) with employer contribution Commuter benefits.

About the job Why Zensar? We're a bunch of hardworking, fun-loving, people-oriented technology enthusiasts. We love what we do, and we're passionate about helping our clients thrive in an increasingly complex digital world. Zensar is an organization focused on building relationships, with our clients and with each other-and happiness is at the core of everything we do. In fact, we're so into happiness that we've created a Global Happiness Council, and we send out a Happiness Survey to our employees each year. We've learned that employee happiness requires more than a competitive paycheck, and our employee value proposition-grow, own, achieve, learn (GOAL)-lays out the core opportunities we seek to foster for every employee. Teamwork and collaboration are critical to Zensar's mission and success, and our teams work on a diverse and challenging mix of technologies across a broad industry spectrum. These industries include banking and financial services, high-tech and manufacturing, healthcare, insurance, retail, and consumer services. Our employees enjoy flexible work arrangements and a competitive benefits package, including medical, dental, vision, 401(k), among other benefits. If you are looking for a place to have an immediate impact, to grow and contribute, where we work hard, play hard, and support each other, consider joining team Zensar! Zensar is seeking an Senior Snowflake Data Engineer -Santa Clara, CA-Work from office all 5 days-This is open for Full time with excellent benefits and growth opportunities and contract role as well. Job Description: Key Requirements: Strong hands-on experience in data engineering using Snowflake with proven ability to build and optimize large-scale data pipelines. Deep understanding of data architecture principles, including ingestion, transformation, storage, and access control. Solid experience in system design and solution architecture, focusing on scalability, reliability, and maintainability. Expertise in ETL/ELT pipeline design, including data extraction, transformation, validation, and load processes. In-depth knowledge of data modeling techniques (dimensional modeling, star, and snowflake schemas). Skilled in optimizing compute and storage costs across Snowflake environments. Strong proficiency in administration, including database design, schema management, user roles, permissions, and access control policies. Hands-on experience implementing data lineage, quality, and monitoring frameworks. Advanced proficiency in SQL for data processing, transformation, and automation. Experience with reporting and visualization tools such as Power BI and Sigma Computing. Excellent communication and collaboration skills, with the ability to work independently and drive technical initiatives. Zensar believes that diversity of backgrounds, thought, experience, and expertise fosters the robust exchange of ideas that enables the highest quality collaboration and work product. Zensar is an equal opportunity employer. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Zensar is committed to providing veteran employment opportunities to our service men and women. Zensar is committed to providing equal employment opportunities for persons with disabilities or religious observances, including reasonable accommodation when needed. Accommodations made to facilitate the recruiting process are not a guarantee of future or continued accommodations once hired. Zensar does not facilitate/sponsor any work authorization for this position. Candidates who are currently employed by a client or vendor of Zensar may be ineligible for consideration. Zensar values your privacy. We'll use your data in accordance with our privacy statement located at: *********************************

Requirements 7 years of experience working as a GenAI Data Science. Experience with Python from a functional programming paradigm, able to manage dependencies and virtual environments, along with version control in git Experience with sequential algorithms (e.g., LSTM, RNN, transformer, etc.) Experience with Bedrock, JumpStart, HuggingFace Experience evaluating ethical implications of AI and controlling for them (e.g., red-teaming) Expertise in supervised learning and unsupervised learning along with experience in deep learning and transfer learning Experience in generative algorithms (e.g., GAN, VAE, etc.) as well as pre-trained models (e.g., LLaMa, SAM, etc.) Experience developing models from inception to deployment

Salary: $200-250k base + RSUs This fast-growing Series E AI SaaS company is redefining how modern engineering teams build and deploy applications. We're expanding our data science organization to accelerate customer success after the initial sale-driving onboarding, retention, expansion, and long-term revenue growth. About the Role As the senior data scientist supporting post-sales teams, you will use advanced analytics, experimentation, and predictive modeling to guide strategy across Customer Success, Account Management, and Renewals. Your insights will help leadership forecast expansion, reduce churn, and identify the levers that unlock sustainable net revenue retention. Key Responsibilities Forecast & Model Growth: Build predictive models for renewal likelihood, expansion potential, churn risk, and customer health scoring. Optimize the Customer Journey: Analyze onboarding flows, product adoption patterns, and usage signals to improve activation, engagement, and time-to-value. Experimentation & Causal Analysis: Design and evaluate experiments (A/B tests, uplift modeling) to measure the impact of onboarding programs, success initiatives, and pricing changes on retention and expansion. Revenue Insights: Partner with Customer Success and Sales to identify high-value accounts, cross-sell opportunities, and early warning signs of churn. Cross-Functional Partnership: Collaborate with Product, RevOps, Finance, and Marketing to align post-sales strategies with company growth goals. Data Infrastructure Collaboration: Work with Analytics Engineering to define data requirements, maintain data quality, and enable self-serve dashboards for Success and Finance teams. Executive Storytelling: Present clear, actionable recommendations to senior leadership that translate complex analysis into strategic decisions. About You Experience: 6+ years in data science or advanced analytics, with a focus on post-sales, customer success, or retention analytics in a B2B SaaS environment. Technical Skills: Expert SQL and proficiency in Python or R for statistical modeling, forecasting, and machine learning. Domain Knowledge: Deep understanding of SaaS metrics such as net revenue retention (NRR), gross churn, expansion ARR, and customer health scoring. Analytical Rigor: Strong background in experimentation design, causal inference, and predictive modeling to inform customer-lifecycle strategy. Communication: Exceptional ability to translate data into compelling narratives for executives and cross-functional stakeholders. Business Impact: Demonstrated success improving onboarding efficiency, retention rates, or expansion revenue through data-driven initiatives.

Staff Data Scientist | San Francisco | $250K-$300K + Equity We're partnering with one of the fastest-growing AI companies in the world to hire a Staff Data Scientist. Backed by over $230M from top-tier investors and already valued at over $1B, they've secured customers that include some of the most recognizable names in tech. Their AI platform powers millions of daily interactions and is quickly becoming the enterprise standard for conversational AI. In this role, you'll bring rigorous analytics and experimentation leadership that directly shapes product strategy and company performance. What you'll do: Drive deep-dive analyses on user behavior, product performance, and growth drivers Design and interpret A/B tests to measure product impact at scale Build scalable data models, pipelines, and dashboards for company-wide use Partner with Product and Engineering to embed experimentation best practices Evaluate ML models, ensuring business relevance, performance, and trade-off clarity What we're looking for: 5+ years in data science or product analytics at scale (consumer or marketplace preferred) Advanced SQL and Python skills, with strong foundations in statistics and experimental design Proven record of designing, running, and analyzing large-scale experiments Ability to analyze and reason about ML models (classification, recommendation, LLMs) Strong communicator with a track record of influencing cross-functional teams If you're excited by the sound of this challenge- apply today and we'll be in touch.

The Company: A data services company based in the heart of San Francisco, are looking for a Senior Data Engineer. They are a team of passionate engineers and data experts that are working on a variety of different project, primarily in the financial services sector, helping organizations build scalable, modern data platforms. This is a hands-on, full-time role with close collaboration alongside the CTO and senior engineers, offering strong influence over technical direction and delivery. The Role: This is an on-site position in the downtown San Francisco where you will be working as part of a close-knit team, collaborating on projects in their brand new office. You will be working across end-to-end data projects, including: Building and maintaining data pipelines and ETL processes. Sourcing and integrating third-party APIs and datasets. Batch and near-real-time processing (cloud agnostic). Downstream analytics and reporting using tools like Sigma Computing and Omnium Analytics. Collaborating with the CTO and engineering team to deliver client solutions. Key Skills: 5+ years' data engineering experience Strong Python, BigQuery, and cloud (GCP or similar) Solid ETL and pipeline background Comfortable with large-scale data Nice to Have Beam, Dataflow, Spark, or Hadoop Tableau or Looker ML/AI exposure Kafka or Pub/Sub Given the varied nature of the work, a broad range of technology experience is valued. You don't need to have experience with every tool listed below to be considered, so we encourage you to apply. This role is 5 days a week on-site in downtown San Francisco. Looking to pay between $170,000-$220,000 with a bonus between 15-20%. Benefits Health, Dental & Vision covered Unlimited PTO 401(k) with employer contribution Commuter benefits.

Salary: $200-250k base + RSUs This fast-growing Series E AI SaaS company is redefining how modern engineering teams build and deploy applications. We're looking for a Staff Data Scientist to drive Sales and Go-to-Market (GTM) analytics, applying advanced modeling and experimentation to accelerate revenue growth and optimize the full sales funnel. About the Role As the senior data scientist supporting Sales and GTM, you will combine statistical modeling, experimentation, and advanced analytics to inform strategy and guide decision-making across our revenue organization. Your work will help leadership understand pipeline health, predict outcomes, and identify the levers that unlock sustainable growth. Key Responsibilities Model the Business: Build forecasting and propensity models for pipeline generation, conversion rates, and revenue projections. Optimize the Sales Funnel: Analyze lead scoring, opportunity progression, and deal velocity to recommend improvements in acquisition, qualification, and close rates. Experimentation & Causal Analysis: Design and evaluate experiments (A/B tests, uplift modeling) to measure the impact of pricing, incentives, and campaign initiatives. Advanced Analytics for GTM: Apply machine learning and statistical techniques to segment accounts, predict churn/expansion, and identify high-value prospects. Cross-Functional Partnership: Work closely with Sales, Marketing, RevOps, and Product to influence GTM strategy and ensure data-driven decisions. Data Infrastructure Collaboration: Partner with Analytics Engineering to define data requirements, ensure data quality, and enable self-serve reporting. Strategic Insights: Present findings to executive leadership, translating complex analyses into actionable recommendations. About You Experience: 6+ years in data science or advanced analytics roles, with significant time spent in B2B SaaS or developer tools environments. Technical Depth: Expert in SQL and proficient in Python or R for statistical modeling, forecasting, and machine learning. Domain Knowledge: Strong understanding of sales analytics, revenue operations, and product-led growth (PLG) motions. Analytical Rigor: Skilled in experimentation design, causal inference, and building predictive models that influence GTM strategy. Communication: Exceptional ability to tell a clear story with data and influence senior stakeholders across technical and business teams. Business Impact: Proven record of driving measurable improvements in pipeline efficiency, conversion rates, or revenue outcomes.

Requirements 7 years of experience working as a GenAI Data Science. Experience with Python from a functional programming paradigm, able to manage dependencies and virtual environments, along with version control in git Experience with sequential algorithms (e.g., LSTM, RNN, transformer, etc.) Experience with Bedrock, JumpStart, HuggingFace Experience evaluating ethical implications of AI and controlling for them (e.g., red-teaming) Expertise in supervised learning and unsupervised learning along with experience in deep learning and transfer learning Experience in generative algorithms (e.g., GAN, VAE, etc.) as well as pre-trained models (e.g., LLaMa, SAM, etc.) Experience developing models from inception to deployment

Staff Data Scientist | San Francisco | $250K-$300K + Equity We're partnering with one of the fastest-growing AI companies in the world to hire a Staff Data Scientist. Backed by over $230M from top-tier investors and already valued at over $1B, they've secured customers that include some of the most recognizable names in tech. Their AI platform powers millions of daily interactions and is quickly becoming the enterprise standard for conversational AI. In this role, you'll bring rigorous analytics and experimentation leadership that directly shapes product strategy and company performance. What you'll do: Drive deep-dive analyses on user behavior, product performance, and growth drivers Design and interpret A/B tests to measure product impact at scale Build scalable data models, pipelines, and dashboards for company-wide use Partner with Product and Engineering to embed experimentation best practices Evaluate ML models, ensuring business relevance, performance, and trade-off clarity What we're looking for: 5+ years in data science or product analytics at scale (consumer or marketplace preferred) Advanced SQL and Python skills, with strong foundations in statistics and experimental design Proven record of designing, running, and analyzing large-scale experiments Ability to analyze and reason about ML models (classification, recommendation, LLMs) Strong communicator with a track record of influencing cross-functional teams If you're excited by the sound of this challenge- apply today and we'll be in touch.