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 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
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 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
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
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