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we are seeking an experienced data scientist to join our Model Validation team. The ideal candidate will bring a blend of data science knowledge and analytical skills, understanding in Finance and an understanding of the regulatory landscape of credit lending. As a core team member, you will work closely with model developers to assess model performance, data quality, conceptual soundness, and produce thorough, compliant documentation for regulatory review, ensuring our models meet the highest standards. You will be required to challenge the models, helping our company deliver high-quality validated models for loan pricing and underwriting.
Key Responsibilities:
Conduct thorough validation of ML models to assess performance, data quality, robustness, conceptual soundness, regulatory requirements and more
Conduct independent tests to assess performance and limitations, and establish model assumptions
Suggest and develop alternative models to challenge and improve existing models
Provide insights into the' strengths and weaknesses of models in terms of Data Science methodology and Finance as well as recommend practical solutions.
Prepare comprehensive validation documentation
Support the ongoing monitoring and improvement of existing predictive models
Stay updated on the latest research in ML credit risk modeling and financial news, ensuring that our practices align with industry standards.

We are seeking an experienced and visionary Data Scientist to join our dynamic technology organization. The successful candidate will be a part of a team of talented data scientists, driving innovation and delivering business value through advanced machine learning techniques and Generative AI solutions. This role requires a strategic thinker with hands-on expertise in both traditional and cutting-edge data science methodologies, and a passion for continuous learning and development.
Responsibilities:
Gradient boosting techniques (e.g., XGBoost, LightGBM, CatBoost) are used to enhance predictive accuracy and model robustness.
Drive the exploration and integration of Generative AI applications, including Large Language Models (LLMs), to create innovative solutions for our products and services.
Collaborate with cross-functional teams (engineering, product, business) to translate business requirements into actionable data science projects.
Establish best practices for model development, validation, deployment, and monitoring in production environments.
Promote a data-driven culture, encouraging experimentation, sharing of knowledge, and adoption of state-of-the-art technologies.
Communicate project progress, insights, and results to stakeholders at all levels of the organization. Design, implement, and optimize classic machine learning models to solve complex business problems.

our company- Crafting Tomorrow's Retail Experience
We started with a simple question: How can vision AI make shopping better for everyone? Today, our team of passionate experts is transforming how people shop and how retailers operate- one store at a time
Our goal is to solve real retail challenges by developing advanced computer vision AI that prevents loss, enables grab-and-go shopping, and turns store data into valuable insights-all while delivering clear value from day one.
With multiple deployments in stores globally, deep partnerships with top-tier retailers, and a product suite thats proving its impact every day, we are not just imagining the future of retail- we're building it.
At our company, were revolutionizing the way people shop with our cutting-edge AI-driven technology, enabling cashier-less stores and advanced theft prevention systems.
We are looking for an experienced, sharp-minded and detail-oriented Data Scientist to join our growing R&D department, and work with an amazing team towards combating retail shrink - that is, catching thieves!
In this role you will develop and implement machine learning models and data-driven algorithms, create methodologies, and employ advanced data analysis techniques to define KPIs, measure our companys performance, and uncover actionable insights that drive impactful research. Your work will focus on transforming vast amounts of data into meaningful predictions, building scalable ML solutions, and enabling tools that improve the effectiveness of our innovative systems.
If you have a passion for data science and advanced analysis of systems solving real-world problems, wed love to hear from you!
A day in the life
Employ accurate data analysis techniques to evaluate system performance and identify areas for improvement. Produce clear, actionable insights to guide innovation and improve product KPIs.
Design and implement algorithms to automate and optimize performance measurement and decision-making processes.
Develop, train, and deploy predictive models that enhance our companys core capabilities.
Continuously monitor, validate, and refine models in production to ensure accuracy and robustness.
Collaborate with algorithm researchers, product managers, and Operations to align model design with business and R&D goals.

The Data Science department plays a pivotal role in our company, generating value by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making.
What You'll Be Doing
Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities

Were looking for a Data Researcher to join the AI Research Team and spread our power. In this role, youll push the boundaries of data security and insight extraction in cloud environments. You'll be at the forefront of developing sophisticated methods to classify and secure sensitive data, addressing challenges like unstructured data and document files. Operate at a large scale and collaborate with some of the largest customers in the world.
WHAT YOULL DO
Develop advanced classification tools and methodologies to accurately identify sensitive data stored in cloud service providers like AWS, Azure, and GCP.
Research and analyze sensitive data, including the identification of Personally Identifiable Information (PII) and secrets such as passwords and API tokens, across both structured (e.g., JSON, CSV) and unstructured formats (e.g., code, text).
Identify and assess data security risks and use cases within cloud environments.
Collaborate with data scientists, engineering, and product teams to drive data-driven product decisions for large-scale projects, working closely with our biggest customers.
Leverage Large Language Models (LLMs) and advanced AI technologies to enhance data processing and analytical workflows, improving efficiency and accuracy.

We are looking for an experienced Data Scientist who can leverage and develop innovative machine learning, NLP, and generative AI technologies, for solving problems within a wide scope.
As a part of our Data Science group, you will work on highly complicated challenges, from research to production, and help shape our algorithms and AI platform. You will work with Developers, Analysts, Product Managers, and business owners on growth opportunities and new ideas.
You should have a strong background and experience in the machine learning pipeline through business understanding, research, data exploration, feature engineering, model building, performance evaluation, testing, production-level code and deployment, model monitoring, and maintenance.
What am I going to do?
Take leading roles in projects such as search engine ranking, promoted ads in our companys search results, recommendations, users segmentation and personalization, online bidding optimization, text analysis, real-time predictions, live streaming data handling, exploration-exploitation problems, etc.
Work closely with various departments in the company to provide advanced Data Science solutions end to end.
Write and own production models and code.
Independent research and innovation in new content and technological domains.
Lead and advise other team members.
Continuously produce new initiatives and improvement ideas.
Act as a leader of our companys AI platform. Develop models and framework solutions for the group.

We are looking for an experienced Data Scientist who can leverage and develop innovative machine learning, NLP, and generative AI technologies, for solving problems within a wide scope. As a part of our Data Science group, you will work on highly complicated challenges, from research to production, and help shape our algorithms and AI platform. You will work with Developers, Analysts, Product Managers, and business owners on growth opportunities and new ideas. You should have a strong background and experience in the machine learning pipeline through business understanding, research, data exploration, feature engineering, model building, performance evaluation, testing, production-level code and deployment, model monitoring, and maintenance.

What am I going to do?:

* Take leading roles in projects such as search engine ranking, promoted ads in Fiverr’s search results, recommendations, users segmentation and personalization, online bidding optimization, text analysis, real-time predictions, live streaming data handling, exploration-exploitation problems, etc.
* Work closely with various departments in the company to provide advanced Data Science solutions end to end.
* Write and own production models and code.
* Independent research and innovation in new content and technological domains.
* Lead and advise other team members.
* Continuously produce new initiatives and improvement ideas.
* Act as a leader of Fiverr’s AI platform. Develop models and framework solutions for the group.

Equal opportunities:
At Fiverr, we prioritize diversity. We celebrate difference and embed it into every aspect of our workplace, from our community to our product. Fiverr is proud and committed to providing equal opportunity employment to all individuals regardless of race, color, religion, sex, sexual orientation, citizenship, national origin, disability, Veteran status, or any other characteristic protected by law. In addition, Fiverr will provide accommodation to individuals with disabilities or a special need.

Were looking for a Data Scientist to join our Data Labs department, which specializes in professional services for our super premium customers.
This role will report to our Datalabs Team Manager in the, R&D.
Why is this role so important?
We are a data-focused company, and our unique AI and machine learning capabilities are the center of our business.
As part of this role, you will create data models that help analyze the petabytes of data we receive from various sources, and research and develop new features and capabilities for our product solutions
As a data scientist in the Datalabs team, you will work on the very core of the company. Part of your role will be to turn raw data into usable metrics and develop new models and statistical algorithms to support out-of-the box requests from customers who want custom digital insights. The Datalabs departments customer centric and business-oriented nature also means you will be supporting a team of data analysts and consultants who interact directly with customers. Together with them, you will translate the voice of these customers into best-in-class digital insights.
So, what will you be doing all day?
Your role as part of the R&D department, and as part of the Datalabs team means your daily responsibilities may include:
Working on versatile use cases within a dynamic, fast paced production environment
Strategic thinking and problem solving, with a strong business sense
Analyzing data from various sources, and turning it into usable input
Understanding various use cases from different customers, and creating models that can translate these cases into meaningful insights
Initiating newly defined tasks from exploration to proof of concept
Owning the finalization of defined tasks (from POC to deployment in production)
Collaborating with data engineers to make sure we reach the desired production results
Owning the ongoing validation process for existing metrics
Collaborating and brainstorming best practices with other teams within the R&D department
Deploying machine-learning models into production for an ongoing use.

Were looking for an Applied Data Scientist to join one of our product squads. Youll design, build, and deploy data-driven solutions that combine machine learning, statistical methods, and SQL/rules-based decision logic to power autonomous supply chain intelligence platform. Youll work closely with data science, engineering, product, and supply chain experts and own solutions end-to-end-from problem definition to production monitoring and iteration.
Responsibilities:
Deliver data science solutions end-to-end within a product squad: problem framing → data prep/labeling → modeling → deployment support → monitoring → iteration
Build, train, and improve ML models for supply chain use cases (e.g., inventory risk prediction, demand anomalies, root-cause analysis)
Define success metrics and evaluation plans with support from senior DS/PM; run error analysis and document learnings
Work with stakeholders to create and maintain ground truth (label definitions, labeling workflows, QA checks, feedback loops)
Implement hybrid decision logic by combining ML outputs with statistical methods and SQL/rules-based logic for robustness and explainability
Analyze large, multi-source operational datasets to identify trends, anomalies, and drivers of performance
Collaborate with software engineers to productionize solutions (batch and/or real-time), including testing, logging, and basic monitoring
Monitor deployed models/rules, investigate performance issues (data quality, drift, edge cases), and iterate based on outcomes
Contribute to team practices: reproducible notebooks/code, documentation, and experiment tracking

We are s looking for a Data Scientist to join our team.
The ideal candidate is a highly motivated and self-driven individual with strong analytical and problem-solving skills. The Data Scientist will be responsible for analyzing data and developing models to help inform decisions and strategies for new products and business initiatives.
Responsibilities:
Work closely with stakeholders to understand business requirements and develop predictive models to detect fraud.
Develop and implement statistical models, machine learning and deep learning algorithms to solve complex problems in a production environment.
Perform exploratory data analysis and data visualization to gain insights and communicate findings.
Collaborate with cross-functional teams, including data engineers and software developers, to design and implement end-to-end solutions that can be deployed in production.
Implement advanced analytics tools and technologies to enhance reporting capabilities.