Nift is building a performance marketplace that helps brands acquire new customers through thoughtful “thank-you” gifts delivered to millions of consumers each month. Our marketplace determines which brands are shown to which consumers and at what price, creating a dynamic system where data, experimentation, and economics directly drive revenue outcomes. 

We are looking for a Senior Revenue & Growth Analyst to help us understand and optimize the marketplace economics. 

In this role, you will analyze how Nift’s auction systems, pricing dynamics, and experimentation frameworks impact brand performance, consumer engagement, and company revenue. You will translate complex system behavior into clear actionable insights. You will partner with Sales, Product, and Data Science to guide product decisions and explain marketplace performance to brand partners.

This is a high-impact role for someone who enjoys solving complex business problems with data, working across teams, and turning analytical insights into decisions that influence revenue.

Our Mission: 

Nift’s mission is to reshape how people discover and try new brands by introducing them to new products and services through thoughtful "thank-you" gifts. Our customer-first approach ensures businesses acquire new customers efficiently while making customers feel valued and rewarded.

We are a data-driven, cash-flow-positive company that has experienced 731% growth over the last three years. As we scale, data and analytics are central to how we make decisions, improve performance, and explain value to our partners.

Backed by investors who supported Fitbit, Warby Parker, and Twitter, we are poised for exponential growth and ready to demonstrate impact on a global scale. Read more about our growth here. 

What you will do:

• Analyze the economics and performance of Nift’s marketplace and auction systems
• Identify drivers of brand performance, pricing efficiency, and customer acquisition outcomes
• Evaluate experiments, model calibration changes, and feature launches
• Partner with our revenue team to provide insights, explain marketplace behavior and performance trends, pricing dynamics to brands
• Perform root-cause analysis, investigate unexpected revenue shifts, performance changes, and anomalies
• Define and track key revenue, marketplace health, and growth metrics
• Translate complex analyses into clear narratives and recommendations
• Collaborate with Product and Data Science to improve marketplace performance and optimization strategies by measuring A/B tests, model calibration changes, and feature launches
• Ensure data accuracy, consistency, and trust across all analyses and deliverables

What you need:

• 5–7+ years of experience in data analytics, growth analytics, or revenue analytics
  
• Strong proficiency in SQL and comfort working with large, complex datasets
• Working knowledge of experimentation analysis (A/B tests) and performance measurement
• Strong analytical thinking and ability to perform root-cause analysis and causal reasoning
  
• Strong business intuition and ability to connect data to revenue outcomes
  
• Excellent communication skills and ability to explain analytical insights to non-technical stakeholders
  
• Ability and desire to work cross-functionally with product, sales, or revenue teams
  

Nice to have:

• Experience with marketplaces, pricing systems, or auction dynamics
  
• Background in growth analytics, adtech, or performance marketing
  
• Experience using Python or R for exploratory analysis
• Experience supporting client-facing teams with data-driven insights
  

What you get:

• Competitive compensation, comprehensive benefits (401(k) with matching, Medical/Dental/Vision), and we offer full-time employees the potential to hold company equity
• Unlimited Responsible PTO
• Direct exposure to product, sales, and leadership with clear ownership and visibility
• High visibility across product, sales, and leadership
  
• Work on marketplace economics and pricing systems
• Direct impact on revenue and marketplace performance
  

Nift is disrupting performance marketing, delivering millions of new customers to brands every month. We’re actively looking for a hands-on Senior Data Scientist to focus on building ML models for scalable consumer-based services (or non-consumer services that require highly scalable ML models for predictions and classifications).

As a Senior Data Scientist, you’ll report to the Data Science Manager and work closely with both our Data Science and Engineering teams. You will play a crucial role in developing models for complex parts of our business. You will analyze large datasets, identify patterns, and develop a variety of model types. You’ll also contribute to the improvement and re-design of our current models. You will collaborate closely with cross-functional teams to translate insights into actionable solutions. This is a hands-on position where you will apply your expertise in statistical modeling, machine learning, and data mining techniques.

This role is ideally based in Israel, but strong candidates from the U.S. will also be considered.

Our Mission: 

Nift’s mission is to reshape how people discover and try new brands by introducing them to new products and services through thoughtful "thank-you" gifts. Our customer-first approach ensures businesses acquire new customers efficiently while making customers feel valued and rewarded.

We are a data-driven, cash-flow-positive company that has experienced 731% growth over the last three years. Now, we’re scaling to become one of the largest sources for new customer acquisition worldwide. Backed by investors who supported Fitbit, Warby Parker, and Twitter, we are poised for exponential growth and ready to demonstrate impact on a global scale. Read more about our growth here.

What you will do:

• Data Analysis and Exploration: You will need to explore and analyze large volumes of data to gain insights and identify patterns relevant to your modeling objectives. This involves data cleaning, preprocessing, and transforming data into a suitable format for modeling
• Model Development: You will design and develop models using statistical and machine-learning techniques. This includes selecting appropriate algorithms, feature engineering, model training, and evaluation
• Data Preparation: You will be responsible for preparing the data required for modeling, including gathering and integrating data from various sources, ensuring data quality and consistency, and defining appropriate features and variables
• Model Evaluation and Testing: You will assess the performance and accuracy of the models using appropriate evaluation metrics. This includes conducting experiments, cross-validation, and measuring the effectiveness of recommendations
• Optimization and Tuning: You will fine-tune models to optimize their performance, improve accuracy, reduce bias or overfitting, and enhance the efficiency of the algorithms. provide actionable recommendations
• Analyze large datasets to identify patterns, trends, and insights that can be leveraged to improve business performance
• Design, build and evaluate systems to personalize consumer experience and drive customer engagement
• Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions
• Conduct rigorous testing and validation of models to ensure their accuracy, robustness, and reliability
• Monitor model performance, identify areas of improvement, and continuously refine models based on new data and evolving business needs
• Stay up-to-date with the latest advancements in data science, machine learning, and recommendation system technologies, and apply them to solve business challenges 

What You Need:

• Master's or Ph.D. in a quantitative field such as Computer Science, Statistics, Applied Mathematics, Economics, Physics, or a related discipline
• 5+ years of experience working in a professional setting deploying models
• Strong experience in building and deploying into production predictive models and recommendation systems using statistical modeling, machine learning, and data mining techniques
• Proficiency in Machine Learning: You should have a deep experience with various machine learning techniques, such as regression, classification, clustering, dimensionality reduction, and ensemble methods. Familiarity with popular algorithms like decision trees, random forests, Boosted trees, and regularized regression.
• Experience with match-propensity models, embeddings based models, cold-start handling, calibration/post-processing, integrating models into ad-tech workflows and business logic, measuring model performance within ad-tech systems.
• Strong Background in Statistics and Mathematics: A solid foundation in statistical concepts, linear algebra, calculus, and probability theory is essential for understanding the principles behind machine learning algorithms and recommendation systems
• Proficiency in programming languages such as Python or R, along with experience in data manipulation and analysis using libraries like NumPy, Pandas, or SciPy
• Solid understanding of data preprocessing, feature engineering, and model evaluation techniques
• Experience in ad-tech is a must, media/advertising platforms, demand-side platforms and supply-side platforms in digital advertising or retail-media networks
• Familiarity with big data technologies and distributed computing frameworks (e.g., Hadoop, Spark) is a plus
• Problem-solving skills and the ability to think critically to develop innovative solutions
• Excellent communication and collaboration skills to effectively work with cross-functional teams and present complex findings

What you get: 

• Competitive compensation, flexible remote work
• Unlimited Responsible PTO
• Great opportunity to join a growing, cash-flow-positive company while having a direct impact on Nift's revenue, growth, scale, and future success