NumPy Jobs in Portugal.
All active NumPy roles based in Portugal.
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Product Analyst, OX
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Highlights:
Location: Portugal, Remote
Language: Russian-speaking team; Professional working proficiency in English (B1 or higher)
About Us
Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.
The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.
We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.
The Team
Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.
We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.
About the Role
As a Product Analyst, you will be a versatile data expert at the heart of our product decisions. Your work will span the full analytical lifecycle—from building data marts and ETL processes to designing and analyzing A/B tests and delivering key insights to stakeholders. This is a role for a proactive analyst who is comfortable working across a wide range of tasks and is passionate about using data to find the truth and drive results.
What You’ll Do
- Uncover Actionable Insights: Identify key trends in user behavior, develop data-backed product hypotheses, and work with teams to test them.
- Own A/B Testing: Design, launch, and analyze A/B tests to validate ideas and optimize product performance.
- Build a Data Foundation: Create and maintain data marts and BI reports to visualize product and operational metrics for the entire company.
- Perform Deep-Dive Analyses: Handle ad-hoc analytical requests to answer critical business and product questions.
Requirements
- 5+ years of professional experience as a Data Analyst or Product Analyst.
- A strong foundation in mathematical statistics and probability theory.
- Advanced proficiency in SQL.
- Expertise in Python and its data analysis libraries (NumPy, Pandas, Matplotlib, Scikit-learn).
- Hands-on experience with BI tools (Tableau, Power BI, Metabase).
- Strong written English for clear documentation and communication.
- A proactive, detail-oriented mindset with a passion for solving complex problems.
Our Tech Stack
- Languages & Libraries: Python
- Databases: ClickHouse, MongoDB, PostgreSQL
- BI & Visualization: Tableau, Grafana
- Orchestration: Airflow
- Version Control: Git
Bonus points
- Curiosity and a hypothesis-driven mindset
- Ability to communicate complex analytical concepts to non-technical audiences
- Detail-oriented with a strong sense of ownership
- Comfort working in fast-paced, data-rich environments
Why work with us
- A strong, collaborative product team that owns what it builds
- Clear product vision and access to real customer feedback from global nonprofit leaders
- Flat structure: no politics, just great work with great people
- Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
- Long-term focus: we offer equity options and value sustained, meaningful contribution
Benefits
- Private medical insurance for the employee and their family
- 22 paid vacation days per year
- Up to 14 paid public holidays per year
- 5 company-paid sick leave days
- English learning courses.
- Relevant professional education.
- Gym or swimming pool.
- Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace.
- Co-working.
- Remote working.
- €50 monthly allowance to cover internet and mobile phone expenses
**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.
We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, disability, or any other characteristic protected by applicable law in the countries where we operate.
Ready to apply?
Apply to Fundraise Up
Product Analytics Team Lead, New Products
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Highlights:
Location: Portugal, Remote
Language: Russian-speaking team; Strong English required (B2)
About Us
Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.
The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.
We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.
The Team
Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.
We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.
About the Role
We’re looking for a Team Lead to join our Product Analytics team for the New Products direction. The New Products direction is our “internal incubator,” responsible for the company’s future revenue. We don’t just improve existing products — we launch entirely new business verticals from scratch.
Currently, we have three key focus areas:
1. P2P (Peer-to-Peer): Building tools for mass fundraising events and marathons (a market with $8M+ ARR potential).
2. Tap-to-Pay & Kiosks: Enabling offline donations via smartphones and physical terminals.
3. Major Donors: Leveraging AI to identify and engage high-value donors.
At the moment, the team consists of one analyst who has already started working on the P2P product.
What You’ll Do
- Act as a right hand to product leads (PMs): help define success criteria for pilots and evaluate whether new products gain traction
- Build analytics from scratch: design data collection systems and ensure reliability monitoring from day one
- Evaluate the performance of new product launches
- Lead and grow the team: mentor team members, run 1:1s, and establish processes in a fast-growing function, as well as plan the roadmap and oversee execution and timelines
Requirements
- 5+ years of experience as a Product Analyst
- 2+ years of team management experience
- Strong knowledge of mathematical statistics and probability theory
- Proficiency in Python (NumPy, pandas, matplotlib, seaborn, scikit-learn)
- Advanced SQL skills
- Experience with BI tools (Tableau, Power BI, Metabase)
Our Tech Stack
- Python
- ClickHouse, MongoDB, PostgreSQL
- Tableau, Grafana
- Airflow
- Git
Bonus points
- Curiosity and a hypothesis-driven mindset
- Ability to communicate complex analytical concepts to non-technical audiences
- Detail-oriented with a strong sense of ownership
- Comfort working in fast-paced, data-rich environments
Why work with us
- A strong, collaborative product team that owns what it builds
- Clear product vision and access to real customer feedback from global nonprofit leaders
- Flat structure: no politics, just great work with great people
- Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
- Long-term focus: we offer equity options and value sustained, meaningful contribution
Benefits
- Private medical insurance for the employee and their family
- 22 paid vacation days per year
- Up to 14 paid public holidays per year
- 5 company-paid sick leave days
- English learning courses.
- Relevant professional education.
- Gym or swimming pool.
- Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace.
- Co-working.
- Remote working.
- €50 monthly allowance to cover internet and mobile phone expenses
**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.
We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, disability, or any other characteristic protected by applicable law in the countries where we operate.
Ready to apply?
Apply to Fundraise Up
Product Analyst, GTM
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Highlights
Location: Portugal, Remote
Language: Russian-speaking team; English proficiency required (C1)
About Us
Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.
The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.
We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.
The Team
Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.
We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.
About the Role
As a Product Analyst, you will be a critical partner to our business teams, working closely with Sales, Marketing, Customer Success (CSM), and Partnerships. Your core mission is to transform raw data into actionable insights that measure effectiveness, drive strategy, and inform the product roadmap. While our development team is Russian-speaking, our main audience and business stakeholders are in the U.S., making your fluency in English essential for success.
What You’ll Do
- Uncover critical insights by forming hypotheses and validating them with data.
- Identify global and local trends in user behavior to inform product decisions.
- Analyze and interpret customer metrics to measure impact and value.
- Design and evaluate A/B tests with prospective customers to optimize performance.
- Handle ad-hoc analytical requests from stakeholders across the organization.
Requirements
- 4+ years of experience as a Data Analyst or Product Analyst.
- A strong foundation in mathematical statistics and probability theory.
- Advanced proficiency in SQL.
- Expertise in Python and its data analysis libraries (NumPy, Pandas, Matplotlib, Scikit-learn).
- Hands-on experience with BI tools (Tableau, Power BI, Metabase).
- Excellent command of written and spoken English (C1 level or higher).
- A proactive, curious mindset with strong analytical and communication skills.
Our Tech Stack
- Languages & Libraries: Python
- Databases: ClickHouse, MongoDB, PostgreSQL
- BI & Visualization: Tableau, Grafana, Metabase
- Orchestration: Airflow
- Version Control: Git
Bonus points
- Curiosity and a hypothesis-driven mindset
- Ability to communicate complex analytical concepts to non-technical audiences
- Detail-oriented with a strong sense of ownership
- Comfort working in fast-paced, data-rich environments
Why work with us
- A strong, collaborative product team that owns what it builds
- Clear product vision and access to real customer feedback from global nonprofit leaders
- Flat structure: no politics, just great work with great people
- Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
- Long-term focus: we offer equity options and value sustained, meaningful contribution
Benefits
- Private medical insurance for the employee and their family
- 22 paid vacation days per year
- Up to 14 paid public holidays per year
- 5 company-paid sick leave days
- English learning courses.
- Relevant professional education.
- Gym or swimming pool.
- Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace.
- Co-working.
- Remote working.
- €50 monthly allowance to cover internet and mobile phone expenses
**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.
We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, disability, or any other characteristic protected by applicable law in the countries where we operate.
Ready to apply?
Apply to Fundraise Up
Product Analyst, Donor Portal
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Highlights:
Location: Portugal, Remote
Language: Russian-speaking team; Professional working proficiency in English (B1 or higher)
About Us
Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.
The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.
We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.
The Team
Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.
We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.
About the Role
We’re looking for a Product Analyst to join the Donor Portal (Donor Experience) team. The Donor Portal team owns the post-donation experience – everything that happens after a donor completes a donation. The team focuses on reducing churn and increasing subscription LTV by improving subscription management within the donor portal (pauses, amount changes, skipping charges, etc.), as well as enhancing donor communications via email.
What You’ll Do
- Run A/B tests
- Identify insights in data, conduct research, and help product teams uncover growth opportunities.
- Work with retention rate and subscription/supporter LTV metrics.
- Design and build data marts.
- Develop and maintain BI dashboards.
- Handle ad-hoc requests from product teams.
Requirements
- 5+ years of professional experience as a Data Analyst or Product Analyst.
- A strong foundation in mathematical statistics and probability theory.
- Advanced proficiency in SQL.
- Expertise in Python and its data analysis libraries (NumPy, Pandas, Matplotlib, Scikit-learn).
- Hands-on experience with BI tools (Tableau, Power BI, Metabase).
- Strong written English for clear documentation and communication.
- A proactive, detail-oriented mindset with a passion for solving complex problems.
Our Tech Stack
- Languages & Libraries: Python
- Databases: ClickHouse, MongoDB, PostgreSQL
- BI & Visualization: Tableau, Grafana
- Orchestration: Airflow
- Version Control: Git
Bonus points
- Curiosity and a hypothesis-driven mindset
- Ability to communicate complex analytical concepts to non-technical audiences
- Detail-oriented with a strong sense of ownership
- Comfort working in fast-paced, data-rich environments
Why work with us
- A strong, collaborative product team that owns what it builds
- Clear product vision and access to real customer feedback from global nonprofit leaders
- Flat structure: no politics, just great work with great people
- Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
- Long-term focus: we offer equity options and value sustained, meaningful contribution
Benefits
- Private medical insurance for the employee and their family
- 22 paid vacation days per year
- Up to 14 paid public holidays per year
- 5 company-paid sick leave days
- English learning courses.
- Relevant professional education.
- Gym or swimming pool.
- Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace.
- Co-working.
- Remote working.
- €50 monthly allowance to cover internet and mobile phone expenses
**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.
We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, disability, or any other characteristic protected by applicable law in the countries where we operate.
Ready to apply?
Apply to Fundraise Up
Cision has one of the largest media and content databases on Earth. Our data science team works on building intelligent and high-impact features driven by machine learning and NLP.
As a Staff Data Scientist, you will be part of our Machine Learning and Data Science team that build and deploy machine learning models used directly in our products. You will work on complex, high-visibility problems and collaborate closely with engineering, product, and analytics teams to turn prototypes into production-grade solutions.
This role is ideal for someone who operates with strong ownership, delivers high-quality work at pace, and acts as a subject-matter expert on key ML components or services.
Key Responsibilities
Develop and deliver complex machine learning and NLP solutions end-to-end.
Analyze large datasets to uncover insights, design features, and guide modeling decisions.
Build, test, and deploy ML models into production systems in partnership with engineering teams.
Work independently to create tools, frameworks, and reusable components that accelerate model development.
Collaborate cross-functionally with product managers, engineers, and analysts to translate prototypes into production-grade models and services.
Demonstrate sound judgment around risk, workload management, prioritization, and escalation.
Act as a go-to SME for your domain and contribute significantly to team commitments and delivery.
Required Qualifications
8+ years of professional experience in a software or ML engineering environment.
5+ years applying advanced statistical or machine learning techniques to real-world business problems.
Advanced degree in a quantitative field (e.g., Statistics, Mathematics, Economics, Computer Science, Machine Learning) or equivalent practical experience.
Proven track record of delivering ML solutions used in production.
Strong proficiency with Python and ML-focused libraries such as Pandas, NumPy, scikit-learn, TensorFlow, or PyTorch.
Hands-on experience with cloud-based ML workflows in GCP and/or AWS (Kubernetes, Nvidia Triton, Vertex AI, Sagemaker, and similar tools)
Proficiency with database query languages (QL) and experience working with large-scale datasets.
Ability to clearly communicate complex technical concepts to non-technical audiences.
Strong sense of ownership, accountability, and commitment to quality.
Preferred Qualifications
Experience with modern NLP techniques and pretrained model ecosystems.
Experience building scalable data pipelines or model-serving architectures.
Familiarity with MLOps concepts and practices.
Experience in building production-quality and scalable inf inerence systems with Python, Java, or general-purpose languages.
What Your Day-to-Day Might Look Like
Experimenting with various modeling techniques using GCP Vertex AI or AWS SageMaker.
Analyzing model performance and implementing strategies to improve accuracy, robustness, and reliability.
Designing and engineering new features based on exploratory data analysis.
Identifying, evaluating, and adapting open-source models to solve NLP and ML tasks.
Partnering with engineers to optimize ML models for deployment and monitoring.
Ready to apply?
Apply to Cision
Cision has one of the largest media and content databases on Earth. Our data science team works on building intelligent and high-impact features driven by machine learning and NLP.
As a Staff Data Scientist, you will be part of our Machine Learning and Data Science team that build and deploy machine learning models used directly in our products. You will work on complex, high-visibility problems and collaborate closely with engineering, product, and analytics teams to turn prototypes into production-grade solutions.
This role is ideal for someone who operates with strong ownership, delivers high-quality work at pace, and acts as a subject-matter expert on key ML components or services.
Key Responsibilities
Develop and deliver complex machine learning and NLP solutions end-to-end.
Analyze large datasets to uncover insights, design features, and guide modeling decisions.
Build, test, and deploy ML models into production systems in partnership with engineering teams.
Work independently to create tools, frameworks, and reusable components that accelerate model development.
Collaborate cross-functionally with product managers, engineers, and analysts to translate prototypes into production-grade models and services.
Demonstrate sound judgment around risk, workload management, prioritization, and escalation.
Act as a go-to SME for your domain and contribute significantly to team commitments and delivery.
Required Qualifications
8+ years of professional experience in a software or ML engineering environment.
5+ years applying advanced statistical or machine learning techniques to real-world business problems.
Advanced degree in a quantitative field (e.g., Statistics, Mathematics, Economics, Computer Science, Machine Learning) or equivalent practical experience.
Proven track record of delivering ML solutions used in production.
Strong proficiency with Python and ML-focused libraries such as Pandas, NumPy, scikit-learn, TensorFlow, or PyTorch.
Hands-on experience with cloud-based ML workflows in GCP and/or AWS (Kubernetes, Nvidia Triton, Vertex AI, Sagemaker, and similar tools)
Proficiency with database query languages (QL) and experience working with large-scale datasets.
Ability to clearly communicate complex technical concepts to non-technical audiences.
Strong sense of ownership, accountability, and commitment to quality.
Preferred Qualifications
Experience with modern NLP techniques and pretrained model ecosystems.
Experience building scalable data pipelines or model-serving architectures.
Familiarity with MLOps concepts and practices.
Experience in building production-quality and scalable inf inerence systems with Python, Java, or general-purpose languages.
What Your Day-to-Day Might Look Like
Experimenting with various modeling techniques using GCP Vertex AI or AWS SageMaker.
Analyzing model performance and implementing strategies to improve accuracy, robustness, and reliability.
Designing and engineering new features based on exploratory data analysis.
Identifying, evaluating, and adapting open-source models to solve NLP and ML tasks.
Partnering with engineers to optimize ML models for deployment and monitoring.
Ready to apply?
Apply to Cision
Senior Data Scientist
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We're a leading SaaS provider revolutionising how fintech companies navigate complex regulatory landscapes. Our platform powers compliance and risk management for hundreds of innovative financial services companies, from emerging startups to established enterprises. We believe in empowering our teams to solve meaningful problems and create exceptional value for our customers.
Role Summary
As a Senior Data Scientist at ComplyAdvantage, you will lead the development and refinement of sophisticated data-driven solutions to detect and prevent financial crime globally. Your core focus is R&D and Strategic Initiatives, where you will spend 80% of your time conducting forward-looking research in ML, NLP, and Agentic AI to create measurable business value over 3-6 month horizons. In addition to driving deep-dive R&D, you will provide expert advisory support and technical leadership to Product and Engineering teams. By leading AI Enablement workstreams, you will empower these departments with the quantitative insights and frameworks necessary to scale high-impact, AI-driven features while mentoring more junior members of the tribe.
Key Responsibilities
- Lead R&D in GenAI and Agentic AI: Design and prototype high-impact, novel solutions for financial crime detection, focusing on multi-agent systems and RAG architectures built on foundational LLM frameworks.
- Drive Production Excellence: Partner with Engineering and Product leadership to architect and oversee the integration of AI components into core product features. You will define the standards for reliability, scalability, and ethical AI performance, ensuring research prototypes transition into robust, production-grade solutions.
- Establish Evaluation Frameworks: Lead the development of robust evaluation methodologies for LLM and agentic AI systems, defining industry-standard metrics for task completion, reasoning accuracy, and system reliability.
- Evaluate Model Context Protocol (MCP): Research applications to connect our AI systems with external data sources and tools, providing strategic recommendations for engineering implementation.
- Strategic Data Insights: Conduct advanced exploratory analysis across multiple data sources to uncover insights that directly influence product development decisions and agent behavior.
- Research & Innovation: Continuously research and evaluate emerging tools and best practices in data science and Agentic AI to keep ComplyAdvantage at the forefront of the field.
- Technical Leadership & Mentoring: Engage across multi-disciplinary teams to share expertise, perform code reviews, and provide career development support to junior data scientists.
Required Qualifications
- MSc or PhD in a numerate subject (e.g., Computer Science, Mathematics, Statistics, Physics) or equivalent practical experience in a data-intensive role.
- 4-7 years of professional experience in data science or machine learning, with a demonstrable impact on production systems.
- Expert-level proficiency in Python, including the core data science ecosystem such as Pandas, NumPy, and Scikit-learn.
- Deep experience with modern ML frameworks (e.g., TensorFlow, PyTorch) for advanced research and prototyping.
- Strong expertise in Agentic AI and LLMs: Advanced knowledge of agentic AI frameworks (e.g., LangChain, Pydantic AI) and experience optimising retrieval systems like RAG.
- Experience with Distributed Computing: Practical knowledge of platforms like Spark or Dask for large-scale data analysis.
- Technical Leadership: Proven track record of leading technical research projects with successful production outcomes and communicating complex concepts to diverse audiences.
Preferred Qualifications
- Experience delivering machine learning solutions and integrating into data pipelines.
- Experience with Natural Language Processing, Entity Resolution, Graph Theory, or Graph Machine Learning.
- Experience working with or evaluating multi-agent systems or complex GenAI workflows.
What Success Looks Like
- In 90 days: You have successfully onboarded, mastered our data landscape, and begun contributing to active research projects while building relationships with key stakeholders.
- In 6 months: You have delivered your first significant research project with measurable impact and established yourself as a technical leader and effective mentor.
- In 12 months: You have led multiple successful R&D initiatives that have shaped our technical roadmap and been recognized as a subject matter expert who empowers other teams.
About Data Science at ComplyAdvantage:
The Data Science tribe discovers and proves out impactful solutions that leverage our Petabyte-scale data infrastructure to neutralise global financial crime. We are responsible for research and development work that drives the "art of the possible" within our product suite. At ComplyAdvantage, we mine the internet for critical data and use it to power a dynamic knowledge graph, which uncovers hidden networks of financial bad actors. From exploring real-time stream processing with Kafka to pioneering the use of the latest LLMs, our modern technology stack allows us to innovate and build prototypes for cutting-edge agentic AI and large-scale algorithmic solutions that empower our clients.
What’s in it for you?
- Equity as we want you to have a part of what we are building
- Private medical insurance designed to keep you ensuring peace of mind while you excel in your career
- Unlimited Time Off Policy- A work-life balance and focus on our well-being are critical to keeping us performing at our best
- We embrace a hybrid approach that requires employees to be in the office for two days a week. We strongly believe that this approach fosters collaboration and enables the building of meaningful relationships
- You will also get a new starter budget to kit out your home office
- Opportunity to work on innovative projects with smart-minded people keen to share their knowledge and continuously improve
- Annual learning budget (prorated based on start date) to drive your performance and career development
About us:
Our mission is to empower every business to eliminate financial crime.
By harnessing AI, a unified platform, and an extensive partner ecosystem, we help customers turn compliance into a catalyst for growth, operational resilience, and enduring regulatory trust.
More than 3,000 enterprises across 75 countries rely on our end-to-end platform and the world’s most comprehensive financial crime risk intelligence. With full-stack agentic automation, we help organizations automate up to 95% of KYC, AML, and sanctions reviews, cut onboarding times by 50%, reduce false positives by 70%, and handle 7x more work with the same staff.
ComplyAdvantage is headquartered in London and has global hubs in New York, Lisbon, Singapore, and Cluj-Napoca. It is backed by Balderton Capital, Index Ventures, Ontario Teachers’ Pension Plan, Goldman Sachs, and Andreessen Horowitz. Learn more about compliance re-engineered for the age of AI at complyadvantage.com.
Ready to apply?
Apply to ComplyAdvantage
The Opportunity
As a Staff Data Scientist at PandaDoc, you will serve as a senior analytical leader, embedding yourself deeply in our product and business data to uncover non-obvious insights and drive actionable recommendations. A primary focus of this strategic role is to champion and drive the organizational shift toward a data-driven culture. You will own the advancement of our experimentation capabilities, train other analysts and data scientists on causal methodologies, and leverage your expertise to provide leadership with a clear, reliable understanding of true impact and causality.
You will report to the Director of GTM Data and act as a strategic thought partner to Go-to-Market teams, Marketing, Product, Finance, Design, Engineering, and executive leadership, ensuring alignment between data insights and critical business decisions.
What You'll Do
Experimentation & Causal Strategy
- Lead the Experimentation Roadmap: Define, champion, and execute a strategic roadmap for measuring impact across PandaDoc, focusing on high-leverage business questions related to customer workflows, churn risk, and long-term value (LTV).
- Advanced Experiment Design: Design, implement, and rigorously analyze complex A/B tests, multivariate experiments, and adaptive experimentation methods, including the application of Bayesian experimentation, to assess the effectiveness of proposed product changes and business levers.
- Causal Inference Beyond A/B: Apply advanced causal inference techniques (e.g., difference-in-differences, synthetic control, propensity score matching, and instrumental variables) to scenarios where randomized controlled trials (RCTs) are infeasible.
- Deep Dive Analysis: Conduct complex, proactive, and exploratory analysis to discover latent user behavior, emerging trends, and root causes of changes in key metrics, translating these findings into actionable product and business insights.
- Develop Measurement Frameworks: Define, instrument, and govern a unified Key Performance Indicator (KPI) framework that maps low-level product health metrics to high-level business outcomes, ensuring consistent and scalable measurement across the organization.
Technical Leadership & Influence
- Scaling Data Science: Partner with Data Engineering to design and build scalable, self-serve experimentation tooling and reusable analytical assets and frameworks (e.g., causal machine learning models) that empower other analysts and data consumers.
- Strategic Influence: Act as a strategic thinker by translating complex statistical findings into clear, compelling, and actionable business narratives for cross-functional partners and senior leadership (VP/C-suite), driving strategic decisions and investment priorities.
- Mentorship and Training: Serve as a technical subject matter expert, training and mentoring junior and mid-level data scientists on best practices in statistical rigor, experimental design, and causal modeling.
About You
Qualifications
- Experience: 6+ years of professional experience in an applied data science, economics, or product analytics role, with a proven track record of leveraging experimentation and causal inference methods to drive significant business impact.
- Education: B.A. or B.S. in Mathematics, Statistics, Economics, Computer Science, or a related quantitative discipline. A Master’s degree in a quantitative field (e.g., Statistics, Data Science, Econometrics, Operations Research) is preferred, but not required.
Required Technical Expertise
- Causal Inference: Demonstrated expertise in applying a wide range of Causal Inference methods, e.g. Quasi-Experimentation, Matching Methods (PSM), Difference-in-Differences, and/or Instrumental Variables.
- Experimentation Methodologies: Expertise in advanced statistical methodologies for A/B testing, including sample size calculations, sequential testing, dealing with interference/network effects, variance reduction techniques (e.g., CUPED), etc.
- Deep Analytical Methods: Mastery of advanced statistical modeling, time-series analysis, and quantitative methods necessary to perform thorough exploratory data analysis, produce timely insights, and provide actionable recommendations.
- Programming: Advanced proficiency in Python or R for statistical modeling, with experience using relevant data science packages (e.g., SciKit-Learn, numpy, pandas).
- Data Tools: Expert-level proficiency in SQL and experience working with established data warehouses (e.g., Snowflake, Postgres).
- Data Pipelining: Experience with data transformation and workflow management tools such as dbt, Airflow, or Databricks is a strong plus.
Key Attributes
- Strategic Communication & Influence: Possesses exceptional communication, presentation, and data storytelling skills with a consistent record of influencing cross-functional partners and leadership at all levels, particularly in navigating and driving consensus in unstructured or ambiguous environments.
- Change Management: Proven ability to drive organizational change management in environments where experimentation and data-driven decision-making are not yet widely adopted.
- Thrive in ambiguity: Ability to navigate significant ambiguity, translate complex business questions into clear analytical frameworks, and manage multiple competing priorities in a fast-paced environment.
- Relevant Experience: Experience in a SaaS domain and a strong focus on Product Data Science are strongly preferred.
Company Culture:
- We're known for our work-life balance, kind co-workers, & creative virtual team-bonding events. And although our Pandas are located across the globe, we stay connected with the help of technology and ensure that everyone on our team feels, well, like a team.
- Pandas work best when they're happy. We retain our talent by upholding our values of integrity & transparency, and selling a product that changes the lives of our customers.
- Check out our LinkedIn to learn more.
Benefits:
- Our benefits include tremendous career growth opportunities, a competitive salary, health and commuter benefits, company paid life & disability, 20+ PTO days, 401K and FSA plans, and of course, a fun team of Pandas to work with!
PandaDoc is an Equal Opportunity Employer. We are committed to equal treatment of all employees without regard to race, national origin, religion, gender, age, sexual orientation, veteran status, physical or mental disability or other basis protected by law.
Ready to apply?
Apply to PandaDoc
Data Scientist
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Role Summary
As a Data Scientist at ComplyAdvantage, you will develop and refine data-driven solutions to detect and prevent financial crime globally. Your core focus is R&D and Strategic Initiatives, conducting forward-looking research in ML, NLP, and Agentic AI to create measurable business value. In addition to deep-dive R&D, you will provide advisory support to Product and Engineering teams. By investing in AI Enablement workstreams, you will empower these departments with the quantitative insights and frameworks necessary to scale high-impact, AI-driven features.
Key Responsibilities
- Advance R&D in GenAI and Agentic AI: Develop high-impact prototypes for financial crime detection, leveraging multi-agent systems and RAG architectures built on foundational LLM frameworks.
- Contribute to Core Solutions: Collaborate with Engineering and Product to integrate and optimise AI components and frameworks into existing and new product features, ensuring reliability, scalability, and ethical performance in production.
- Evaluate LLM-based Systems: Contribute to the development and implementation of robust evaluation methodologies for LLM and agentic AI based systems, tracking key metrics related to task completion, reasoning accuracy, tool effectiveness, and overall reliability.
- Evaluate Model Context Protocol (MCP) applications: Connect our AI systems with external data sources and tools and provide recommendations for engineering implementation
- Data Understanding: Develop a solid understanding of our existing data sources, identifying challenges and suggesting potential improvements.
- Data Analysis: Use exploratory data analysis and data mining techniques to identify actionable insights for product improvement, including patterns that can inform and refine agent behavior and prompt engineering strategies.
- Research & Innovation: Continuously research and evaluate emerging tools, technologies, and best practices in data science, especially within the rapidly evolving field of Agentic AI, to keep ComplyAdvantage at the forefront.
- Cross-Functional Collaboration: Engage effectively with multi-disciplinary teams to actively share best practices, expertise and inspire innovation to foster an AI-first culture across the organization.
- Visualization & Roadmapping: Provide clear data insights and visualizations that will act as a basis for new ideas to be integrated into our product roadmap.
Required Qualifications
- MSc or PhD in a numerate subject (e.g., Computer Science, Mathematics, Statistics, Physics) or equivalent practical experience in a data-intensive role.
- 2-4 years of professional experience in data science or a related field, with a demonstrated ability to contribute to impactful data-driven solutions.
- Proficiency in Python, including experience with core data science libraries (e.g., Pandas, NumPy, Scikit-learn).
- Hands-on experience with modern machine learning frameworks such as TensorFlow or PyTorch.
- Familiarity with the foundational concepts of agentic AI and large language models (LLMs). This can be professional or through personal research.
- Basic understanding of popular agentic AI frameworks (e.g., LangChain, Pydantic AI).
- Knowledge of general evaluation techniques for AI models and an eagerness to learn and apply methods specific to agentic systems.
- Ability to communicate complex technical concepts effectively to a variety of stakeholders.
- Strong passion for data and solving challenging real-world problems using algorithms.
Preferred Qualifications
- Prior experience contributing to the deployment and integration of machine learning models into production data pipelines.
- Exposure to Big Data platforms such as Spark.
- Experience with Natural Language Processing, Entity Resolution, Graph Theory, or Graph Machine Learning.
- Experience working with or evaluating multi-agent systems or complex AI workflows.
What Success Looks Like
- In 90 days: You have successfully onboarded, gaining a clear understanding of our data landscape and current AI frameworks. You are actively contributing to R&D experiments and have established collaborative working relationships with peers in Engineering and Product.
- In 6 months: You have delivered your first significant R&D prototype or technical evaluation. You have begun contributing to our AI Enablement workstreams, perhaps by authoring a technical blog post or internal guide that translates your research findings into actionable knowledge for the wider team.
- In 12 months: You have completed multiple R&D initiatives that have shaped our technical roadmap. You are recognized for empowering other teams through your advisory support and quantitative expertise, consistently providing the "AI-first" insights that help Engineering and Product teams scale high-impact features.
About Data Science at ComplyAdvantage:
The Data Science tribe discovers and proves out impactful solutions that leverage our Petabyte-scale data infrastructure to neutralise global financial crime. We are responsible for research and development work that drives the "art of the possible" within our product suite. At ComplyAdvantage, we mine the internet for critical data and use it to power a dynamic knowledge graph, which uncovers hidden networks of financial bad actors. From exploring real-time stream processing with Kafka to pioneering the use of the latest LLMs, our modern technology stack allows us to innovate and build prototypes for cutting-edge agentic AI and large-scale algorithmic solutions that empower our clients.
What’s in it for you?
- Equity as we want you to have a part of what we are building
- Private medical insurance designed to keep you ensuring peace of mind while you excel in your career
- Unlimited Time Off Policy- A work-life balance and focus on our well-being are critical to keeping us performing at our best
- We embrace a hybrid approach that requires employees to be in the office for two days a week. We strongly believe that this approach fosters collaboration and enables the building of meaningful relationships
- You will also get a new starter budget to kit out your home office
- Opportunity to work on innovative projects with smart-minded people keen to share their knowledge and continuously improve
- Annual learning budget (prorated based on start date) to drive your performance and career development
About us:
Our mission is to empower every business to eliminate financial crime.
By harnessing AI, a unified platform, and an extensive partner ecosystem, we help customers turn compliance into a catalyst for growth, operational resilience, and enduring regulatory trust.
More than 3,000 enterprises across 75 countries rely on our end-to-end platform and the world’s most comprehensive financial crime risk intelligence. With full-stack agentic automation, we help organizations automate up to 95% of KYC, AML, and sanctions reviews, cut onboarding times by 50%, reduce false positives by 70%, and handle 7x more work with the same staff.
ComplyAdvantage is headquartered in London and has global hubs in New York, Lisbon, Singapore, and Cluj-Napoca. It is backed by Balderton Capital, Index Ventures, Ontario Teachers’ Pension Plan, Goldman Sachs, and Andreessen Horowitz. Learn more about compliance re-engineered for the age of AI at complyadvantage.com.
Ready to apply?
Apply to ComplyAdvantage
The Opportunity
As a Staff Data Scientist at PandaDoc, you will serve as a senior analytical leader, embedding yourself deeply in our product and business data to uncover non-obvious insights and drive actionable recommendations. A primary focus of this strategic role is to champion and drive the organizational shift toward a data-driven culture. You will own the advancement of our experimentation capabilities, train other analysts and data scientists on causal methodologies, and leverage your expertise to provide leadership with a clear, reliable understanding of true impact and causality.
You will report to the Director of Product Data and act as a strategic thought partner to Product, Finance, Design, Engineering, Product Marketing, and executive leadership, ensuring alignment between data insights and critical business decisions.
What You'll Do
Experimentation & Causal Strategy
- Lead the Experimentation Roadmap: Define, champion, and execute a strategic roadmap for measuring impact across PandaDoc, focusing on high-leverage business questions related to customer workflows, churn risk, and long-term value (LTV).
- Advanced Experiment Design: Design, implement, and rigorously analyze complex A/B tests, multivariate experiments, and adaptive experimentation methods, including the application of Bayesian experimentation, to assess the effectiveness of proposed product changes and business levers.
- Causal Inference Beyond A/B: Apply advanced causal inference techniques (e.g., difference-in-differences, synthetic control, propensity score matching, and instrumental variables) to scenarios where randomized controlled trials (RCTs) are infeasible.
- Deep Dive Analysis: Conduct complex, proactive, and exploratory analysis to discover latent user behavior, emerging trends, and root causes of changes in key metrics, translating these findings into actionable product and business insights.
- Develop Measurement Frameworks: Define, instrument, and govern a unified Key Performance Indicator (KPI) framework that maps low-level product health metrics to high-level business outcomes, ensuring consistent and scalable measurement across the organization.
Technical Leadership & Influence
- Scaling Data Science: Partner with Data Engineering to design and build scalable, self-serve experimentation tooling and reusable analytical assets and frameworks (e.g., causal machine learning models) that empower other analysts and data consumers.
- Strategic Influence: Act as a strategic thinker by translating complex statistical findings into clear, compelling, and actionable business narratives for cross-functional partners and senior leadership (VP/C-suite), driving strategic decisions and investment priorities.
- Mentorship and Training: Serve as a technical subject matter expert, training and mentoring junior and mid-level data scientists on best practices in statistical rigor, experimental design, and causal modeling.
About You
Qualifications
- Experience: 6+ years of professional experience in an applied data science, economics, or product analytics role, with a proven track record of leveraging experimentation and causal inference methods to drive significant business impact.
- Education: B.A. or B.S. in Mathematics, Statistics, Economics, Computer Science, or a related quantitative discipline. A Master’s degree in a quantitative field (e.g., Statistics, Data Science, Econometrics, Operations Research) is preferred, but not required.
Required Technical Expertise
- Causal Inference: Demonstrated expertise in applying a wide range of Causal Inference methods, e.g. Quasi-Experimentation, Matching Methods (PSM), Difference-in-Differences, and/or Instrumental Variables.
- Experimentation Methodologies: Expertise in advanced statistical methodologies for A/B testing, including sample size calculations, sequential testing, dealing with interference/network effects, variance reduction techniques (e.g., CUPED), etc.
- Deep Analytical Methods: Mastery of advanced statistical modeling, time-series analysis, and quantitative methods necessary to perform thorough exploratory data analysis, produce timely insights, and provide actionable recommendations.
- Programming: Advanced proficiency in Python or R for statistical modeling, with experience using relevant data science packages (e.g., SciKit-Learn, numpy, pandas).
- Data Tools: Expert-level proficiency in SQL and experience working with established data warehouses (e.g., Snowflake, Postgres).
- Data Pipelining: Experience with data transformation and workflow management tools such as dbt, Airflow, or Databricks is a strong plus.
Key Attributes
- Strategic Communication & Influence: Possesses exceptional communication, presentation, and data storytelling skills with a consistent record of influencing cross-functional partners and leadership at all levels, particularly in navigating and driving consensus in unstructured or ambiguous environments.
- Change Management: Proven ability to drive organizational change management in environments where experimentation and data-driven decision-making are not yet widely adopted.
- Thrive in ambiguity: Ability to navigate significant ambiguity, translate complex business questions into clear analytical frameworks, and manage multiple competing priorities in a fast-paced environment.
- Relevant Experience: Experience in a SaaS domain and a strong focus on Product Data Science are strongly preferred.
Company Culture:
- We're known for our work-life balance, kind co-workers, & creative virtual team-bonding events. And although our Pandas are located across the globe, we stay connected with the help of technology and ensure that everyone on our team feels, well, like a team.
- Pandas work best when they're happy. We retain our talent by upholding our values of integrity & transparency, and selling a product that changes the lives of our customers.
- Check out our LinkedIn to learn more.
Benefits:
- Our benefits include tremendous career growth opportunities, a competitive salary, health and commuter benefits, company paid life & disability, 20+ PTO days, 401K and FSA plans, and of course, a fun team of Pandas to work with!
PandaDoc is an Equal Opportunity Employer. We are committed to equal treatment of all employees without regard to race, national origin, religion, gender, age, sexual orientation, veteran status, physical or mental disability or other basis protected by law.
Ready to apply?
Apply to PandaDoc