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As a Data Science Team Leader , you will lead a high-performing team developing AI/ML solutions that secure the digital worlds most sensitive assets. Youll play a key role in driving innovation, productizing machine learning systems, and applying advanced modeling techniques to real-world cybersecurity challenges. In this leadership role, youll balance hands-on technical involvement with strategic oversight, guiding projects from research to production. Youll work closely with data scientists, engineers, analysts, product managers, and Cyber-Security researchers to build intelligent features across identity security portfolio.

Lead, mentor, and grow a team of applied data scientists working on machine learning models that power AI-driven cybersecurity solutions.
Own the end-to-end development lifecycle of AI projects - from exploratory research and experimentation through scalable deployment and optimization.
Partner with engineering and product leadership to define technical strategies, prioritize initiatives, and ensure successful model delivery.
Drive innovation across a broad spectrum of ML domains including supervised/unsupervised learning, anomaly detection and generative AI.
Provide hands-on guidance in model development using tools such as scikit-learn, PyTorch, TensorFlow, and Hugging Face.
Ensure high-quality execution through strong code review practices, reproducibility, and model evaluation frameworks.
Champion best practices in MLOps, data governance, explainability, and monitoring.
Keep pace with academic and industry advances and translate cutting-edge research into productized capabilities.

We are looking for an experienced and passionate Data Engineering Team Leader to lead a team of 5 seasoned data engineers. You will play a critical role in designing and delivering scalable, reliable data infrastructure and ETLs, enabling our machine learning, analytics, and product teams to deliver maximum impact.

Lead and grow a high-performing team of experienced data engineers.
Define and implement the teams technical roadmap, ensuring alignment with AI, Data, and Researchs achieving strategic objectives and product roadmap.
Own the development, and operation of robust, scalable, and efficient data pipelines and services.
Oversee the quality, performance, and maintainability of the teams codebase and delivered solutions.
Manage delivery plans, track progress, resolve blockers, and ensure on-time delivery.
Drive best practices in software engineering, data modeling, data quality, code quality, security, observability, and operational excellence.
Translate business and research requirements into scalable technical data solutions.
Foster a culture of ownership, collaboration, continuous learning, drive improvement and innovation within the team.
Actively mentor team members, guide career development, and conduct regular performance reviews.

we are looking for an experienced and highly motivated Senior Data Engineer with high professional skills to join our AI, Data & Research unit. Spearhead the development of Data Lakehouse processes and modeling products; Define and popularize best practices in the data field.

Work closely with ML, Data engineers and architects from the AI, Data & Research unit as well as R&D software engineering teams.
identify opportunities and help specify data requirements to improve security for products and customers along with product managers and data scientists.

As Senior Data scientist , you will shape the future of identity security and develop innovative AI/ML solutions that enhance security and protect the emerging agentic AI landscape in top organizations. Drive AI research and engineering to address evolving threats and protect critical digital assets effectively.

Drive AI/ML projects from research to production, leveraging advanced algorithms, LLMs, classification models, Unsupervised learning and optimization techniques to enhance cybersecurity solutions.
Model Building: Design, implement, and optimize machine learning models, including deep learning, using frameworks such as PyTorch, TensorFlow, Hugging Face, and scikit-learn.
Work closely with product manager, engineers, software architects and analysts to understand requirements, validate model assumptions, and deliver actionable insights.
Identify AI/ML impact opportunities and translate business needs into actionable roadmap items.
Stay current with the latest advancements in data science and apply best practices to ensure optimal performance

We are looking for a Marketing Analytics team leader to join our team of marketing analysts. The ideal candidate will have a strong background in marketing analysis, combined with leadership experience.
What am I going to do?:
* Lead, manage, and develop a team of marketing analysts
* Oversee data collection, analysis, and reporting to support marketing strategies
* Collaborate with cross-functional teams
* Define KPIs and optimize marketing campaigns
* Drive insights and recommendations to enhance marketing performance
Equal opportunities:
At our company, we prioritize diversity. We celebrate difference and embed it into every aspect of our workplace and product, as well as our community. 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.

As a Data Analyst you will be working with colleagues from various disciplines, such as - Product, Engineering, Marketing, Sales, Customer Success, Risk, Data Scientists within the team and other Data Analysts - on their KPIs, the way they observe information and the hardest questions each team is facing in order to drive insights and keep us a data driven company. You will play a key role in the ability of each team at Melio to keep scaling!

As a Data Engineer Tech Lead, you will play a central role in shaping our data strategy and guiding the team in building and optimizing analytics data pipelines that power business decisions across the organization. Beyond driving complex data initiatives, youll be a hands-on mentor and technical advisor, supporting other data engineers, fostering a culture of collaboration, and ensuring the teams overall growth and success.

Were seeking a highly motivated Director of Analytics with a strong business orientation and deep analytics expertise to elevate our data-driven culture. Youll lead a growing group of analysts, partner with cross-functional teams, and build innovative solutions that power product-led growth strategy and customer experience.
What will you be responsible for?
Lead, mentor, and develop a group of talented analystsensuring professional growth, quality deliverables, and a culture of curiosity.
Define and execute analytics strategies to support PLG motions, drive product adoption, customer retention, and overall business performance.
Champion the integration of AI-powered analytics tools, transforming how we generate insights and scale impact across teams.
Collaborate with Product, Growth, Marketing, and Customer Success to uncover data-driven opportunities and influence key decisions.
Partner with Data Engineering to ensure reliable, scalable infrastructure and tooling for advanced reporting and analytics.
Conduct deep product analyticsanalyzing user journeys, growth funnels, and cohort behavior to drive actionable insights.
Design, implement, and evaluate experiments (A/B tests) to optimize onboarding, activation, monetization, and retention.

We are looking for a Data Backend Engineer.
What will you be responsible for?
Design and build distributed data systems that are the backbone of our product innovation.
Architect and implement high-throughput data pipelines capable of handling billions of records with speed and reliability.
Develop custom algorithms for deduplication, data merging, and real-time data updates.
Optimize storage, indexing, and retrieval strategies to manage massive datasets efficiently.
Solve deep engineering challenges in distributed computing environments like Spark, EMR, and Databricks.
Build fault-tolerant, highly available data infrastructure with integrated monitoring and observability.
Partner closely with ML engineers, backend developers, and product managers to turn business needs into scalable, production-grade features.

Were looking for a Data Engineer to design and implement high-scale, data-intensive platforms, research and develop algorithmic solutions, and collaborate on key company initiatives. You will play a critical role within core data teams, which are responsible for managing and optimizing fundamental data assets.
What will you be responsible for?
Solve Complex Business Problems with Scalable Data Solutions
Develop and implement robust, high-scale data pipelines to power core assets.
Leverage cutting-edge technologies to tackle complex data challenges and enhance business operations.
Collaborate with Business Stakeholders to Drive Impact
Work closely with Product, Data Science, and Analytics teams to define priorities and develop solutions that directly enhance core products and user experience.
Build and Maintain a Scalable Data Infrastructure
Design and implement scalable, high-performance data infrastructure to support machine learning, analytics, and real-time data processing.
Continuously monitor and optimize data pipelines to ensure reliability, accuracy, and efficiency.

We are looking for a Data Engineering Tech Lead.
What will you be responsible for?
Lead the design and development of scalable, high-performance data workflows, including both batch pipelines and real-time data products.
Define, implement, and enforce engineering best practices related to code quality, testing, CI/CD pipelines, observability, and documentation.
Mentor, support, and grow a team of data engineers, fostering a collaborative and high-performance engineering culture.
Identify opportunities to create new data assets and features that expand product capabilities and value proposition.
Drive architectural decision-making in areas of data modeling, storage solutions, and compute resources within cloud environments such as Databricks and Snowflake.
Collaborate closely with cross-functional stakeholdersincluding Product, DevOps, and R&Dto ensure effective delivery and platform stability.
Promote and champion a data-driven mindset across the organization, balancing technical rigor with business context and strategic goals.

Were looking for a Data Engineer for the Insight Team to join Lushas Data Group and a new team responsible for developing innovative features based on multiple layers of data. These features will power recommendation systems, insights, and more. This role involves close collaboration with the core teams within the Data Group, working on diverse data pipelines that tackle challenges related to scale and algorithmic optimization, all aimed at enhancing the data experience for Lushas customers.
What will you be responsible for?
Develop and implement robust, scalable data pipelines and integration solutions within Lushas Databricks-based environment.
Develop models and implement algorithms, with a strong emphasis on delivering high-quality results.
Leverage technologies like Spark, Kafka, and Airflow to tackle complex data challenges and enhance business operations.
Design innovative data solutions that support millions of data points, ensuring high performance and reliability.

We're seeking talented data engineers to join our rapidly growing team, which includes senior software and data engineers. Together, we drive our data platform from acquisition and processing to enrichment, delivering valuable business insights. Join us in designing and maintaining robust data pipelines, making an impact in our collaborative and innovative workplace.

Responsibilities
Design, implement, and optimize scalable data pipelines for efficient processing and analysis.
Build and maintain robust data acquisition systems to collect, process, and store data from diverse sources.
Take part in developing agentic capabilities.
Collaborate with DevOps, Data Science, and Product teams to understand needs and deliver tailored data solutions.
Monitor data pipelines and production environments proactively to detect and resolve issues promptly.
Apply best practices for data security, integrity, and performance across all systems.

We're seeking talented data engineers to join our rapidly growing team, which includes senior software and data engineers. Together, we drive our data platform from acquisition and processing to enrichment, delivering valuable business insights. Join us in designing and maintaining robust data pipelines, making an impact in our collaborative and innovative workplace.

Responsibilities
Design, implement, and optimize scalable data pipelines for efficient processing and analysis.
Build and maintain robust data acquisition systems to collect, process, and store data from diverse sources.
Take part in developing agentic capabilities.
Mentor, support, and guide junior team members, sharing expertise and fostering their professional development.
Collaborate with DevOps, Data Science, and Product teams to understand needs and deliver tailored data solutions.
Monitor data pipelines and production environments proactively to detect and resolve issues promptly.
Apply and be responsible for best practices in data security, integrity, and performance across all systems.

Responsibilities and Duties:

data Integration (60%)
Design, build, and maintain seamless data integrations with customers using Streams, Databases (DBs), and APIs.
Ensure efficient data mapping, transformation, and validation processes.
Optimize integration pipelines for performance and scalability.
Customer Support Issue Resolution (30%)
Troubleshoot and resolve integration or data -related issues for customers.
Act as a trusted technical advisor, helping clients optimize their data processes.
Work closely with Customer Success teams to enhance the onboarding experience and reduce time to value.
Continuous Improvement (10%)
Provide insights to enhance data integration processes, improve system efficiency, and contribute to automation efforts.
Identify opportunities to streamline workflows and implement best practices.