דרושים » תוכנה » Applied Data Scientist

We're hiring an exceptional Applied AI Scientist to join our team!

In this role, you'll design and deploy enterprise-grade AI agents that drive real business impact across Tipalti's core functions - Sales, Marketing, Customer Success, Customer Support, Risk, and Finance. You'll be building agentic systems that execute complex, multi-step business workflows end-to-end. The ideal candidate is a hands-on builder with deep AI expertise who thrives on turning complex business problems into reliable, production-grade AI systems.


In This Role, You Will Be Responsible For


Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions - including lead qualification and outreach (Sales & Marketing), churn reduction(Customer Success), and Ticket deflection (Support).
Agentic Architecture & Orchestration: Owning the end-to-end agent stack - from tool use, memory management, and multi-step planning to human-in-the-loop escalation patterns, guardrails, and audit trails suited for an enterprise fintech environment.
Knowledge Systems: Building and maintaining RAG pipelines that ground agents in proprietary knowledge - product documentation, customer data, financial records, and internal playbooks - using vector databases, hybrid search, and re-ranking.
Evaluation & Continuous Improvement: Defining agent evaluation frameworks that measure task completion, accuracy, hallucination rates, latency, and business impact - then iterating on agent behavior based on real usage data and stakeholder feedback.
Cross-Functional Collaboration: Partnering with stakeholders across the company to define agentic use cases, translate business requirements into technical features, and deliver products that create measurable ROI - from data preprocessing through product deployment.

We're looking for a Senior Data Scientist to join the AI cybersecurity team in the Security and Networking Architecture group. As a Senior Data Scientist youll have the opportunity to take an active part in the research and development of our world-class networking and data center security products. This role involves creative problem solving alongside engineering teams, and is key for the continued success of AI networking security.

What youll be doing:

Developing agentic AI systems for security, combining generative models, RAG, and tool-augmented reasoning to automate threat analysis and response workflows.

Optimizing and fine-tuning models for performance, scalability, and resource utilization, considering factors such as latency, efficiency, and cost.

Developing, implementing and improving models and algorithms across media types, whether time series, images, text, audio or video.

Leveraging data pipelines to efficiently process and transform large volumes of data for training and inference purposes.

Applying alignment techniques and parameter efficient fine-tuning to improve model performance.

Measuring and benchmarking model and application performance to drive improvements.

Driving the gathering, building, and annotation of domain specific datasets for benchmarking and training.

Collaborating closely with software and hardware engineers on new features and improvements. Participate in developing and reviewing code, design documents, use case reviews, and test plan reviews.

Were looking for a Data scientist Expert to join us and spread the power of our company. As a Data Scientist you will be responsible for driving research and development of autonomous AI agents and LLM-powered systems at our company. You will work closely with cross-functional teams to explore, innovate, and implement AI-driven solutions to tackle emerging threats, examine cloud security features, and enhance the companys security posture.
WHAT YOULL DO
Lead applied research on AI agents and LLM-driven features in the company platform - from autonomous threat investigation agents to AI-powered security operations workflows
Cover a range of features - from leveraging LLMs to enhance customer investigation experience to novel usage of AI for cloud security
Collaborate with engineering teams to design, build, and maintain production pipelines
Work closely with the Security Research and Product teams to define research goals
Conduct experiments and evaluate the performance of AI models, algorithms, and techniques using real-world datasets and simulated environments
Stay abreast of cutting-edge AI methodologies, frameworks, and tools and apply them to improve security solutions' accuracy, efficiency, and scalability.

As a Machine Learning Scientist, you will design, build, and deploy advanced models that guide pricing and promotional optimization across us. You will work closely with other scientists, engineers, analysts, and product teams to translate complex business challenges into scalable, data-driven solutions that deliver measurable impact.

Key Job Responsibilities and Duties:

Develop and deploy models for causal inference, uplift estimation, and optimization to measure and maximize the incremental effect of price and promotion decisions.

Design and improve dynamic pricing algorithms that balance competitiveness, conversion, and profitability.

Contribute to the development of platform capabilities, enhancing experimentation, simulation, and decision-support capabilities.

Partner with product and business stakeholders to translate scientific insights into actionable strategies.

Stay up to date with the latest advances in machine learning, causal modeling, and pricing optimization, and apply them pragmatically at scale.

We are looking for an experienced NLP Data Science Team Leader to lead a team of talented NLP Data Scientists and drive the development of cutting-edge NLP solutions at scale. This role combines hands-on technical leadership, people management, and strategic influence over product and research directions.



Responsibilities

Lead and grow a team of NLP Data Scientists
Manage, mentor, and support team members professional development
Foster a culture of excellence, ownership, and continuous learning
Own end-to-end delivery of NLP solutions
Oversee algorithmic features from ideation through research, development, and production
Ensure high-quality, scalable, and maintainable solutions
Drive technical direction and innovation
Guide research efforts and evaluate new NLP/ML technologies
Translate business needs into impactful NLP solutions
Collaborate cross-functionally
Work closely with Product, Engineering, and Business stakeholders
Align team priorities with company goals and product roadmap
Maintain hands-on involvement
Contribute to architecture, modeling, and critical algorithmic challenges
Review code, experiments, and methodologies
Scale impact
Improve processes, workflows, and best practices for research and production
Ensure efficient use of large-scale data and infrastructure

we are 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.

We are looking for an exceptional Deep Learning Engineer to join our core autonomy team. In this role, you will be responsible for building the AI-driven "brain" of our autonomous driving technology. Your focus will be on designing, training, and deploying state-of-the-art Deep Learning models that handle high-level prediction and driving policy. You will solve complex, real-world challenges by leveraging advanced neural network architectures to optimize decision-making under high uncertainty.
Responsibilities
Model Training & Architecture: Design, train, and optimize cutting-edge Deep Learning models for prediction and driving policy.
End-to-End DL Development: Take ownership of the full DL lifecycle, from data curation and feature engineering to training, evaluation, and deployment.
Scalable Infrastructure: Develop robust pipelines for training and evaluating models on massive, real-world driving datasets.
Production Deployment: Optimize and integrate deep learning models to run efficiently in real-time within the core autonomy software stack.
Full-time availability at our Tel Aviv HQ.

The Data Science role is the engine behind our industry-leading Exposure Management (EM) platform.
You will be responsible for the AI models that power our CAASM (Cyber Asset Attack Surface Management) capabilities and our advanced Vulnerability Prioritization and Remediation engines.

We are building the intelligence layer that helps organizations implement a Continuous Threat Exposure Management (CTEM) framework. You will build models that normalize fragmented data from hundreds of sources, calculate complex risk scores, and prioritize which exposures actually pose a threat to the business.

We are looking for an experienced and creative data scientist, with a software development touch, to join our Data Science and our family. A data scientist that understands and loves data, and lots of it.

What you will do...
Solve Applied Product Challenges: Deep-dive into our product ecosystem to identify and solve high-impact problems. You will translate complex customer needs into scalable ML features that directly improve the user experience.
Lead Exposure Intelligence R&D: Develop features that unify asset data (CAASM) with threat intelligence. This includes building models for entity resolution (deduplicating assets across fragmented sources) and automated risk assessment.
Advanced NLP & Knowledge Extraction: Use NLP and LLMs to parse unstructured security data-such as CVEs, threat intel feeds, and security advisories-to automate the mapping of vulnerabilities to specific business contexts.
Predictive Prioritization: Design and optimize algorithms that go beyond static CVSS scores. You will incorporate exploitability (EPSS), reachability, and business criticality to help clients focus on the 1% of exposures that matter most.
End-to-End Ownership: Work closely with Product Managers and Data analysts and Engineers to ensure your models aren't just accurate in a notebook, but are robust, explainable, and deliver clear value within the product UI.
Graph-Based Attack Surface Mapping: Identify hidden patterns and relationships between assets, users, and vulnerabilities to visualize the potential "blast radius" of a security gap.

Required Customer-Facing Data Scientist - Demand Forecasting
Demand Forecasting Team
The Demand Forecasting team is at a pivotal, high-growth stage. We have successfully built our core pipeline and are now aggressively onboarding new, diverse customers. This role is highly dynamic, requiring a blend of technical depth, proactive research, and exceptional communication to adapt our platform to real-world customer data and challenges. You will be a critical link between the core product and our clients business success.
Responsibilities
As a key Customer-Facing Data Scientist on the Demand Forecasting team, you will:
Work at the forefront of the data world, focusing on the optimization and deployment of Demand Forecasting models.
Handle complex data science challenges using state-of-the-art techniques relevant to demand forecasting and time series, such as forecasting model ensembling, anomaly detection, feature engineering for trend/seasonality, and causal inference modeling.
Act as a highly communicative partner to our clients, diving deep into their unique datasets to understand the nuances and challenges of their business.
Lead the rigorous testing and application of our core ML pipeline on new customer data, identifying areas where it performs exceptionally well and researching/developing solutions for complex cases where it does not.
Be instrumental in helping our clients achieve their business goals and realize the measurable value of our Demand Forecasting module.
Work within a production and product-oriented environment, ensuring models are robust, scalable, and directly integrated into the clients operational workflow.

You will be part of a research team, creating and improving our core-data algorithms. This Data Analyst role balances strategic, end-to-end data research with high-velocity, ad-hoc analysis to support crucial engineering and product decisions. You will immerse yourself in the fascinating world of maritime data, using Python, SQL, LLM frameworks, and occasionally Java to conduct analysis and ensure your insights drive strategic product development.



What will you do?

Conduct end-to-end analysis & research to create and improve our core-data algorithms.
Turn signals into actionable insights by analyzing GEOINT, SIGINT, and ADINT, and fusing them with maritime data.
Write Python code to extract and analyze data from various sources (including Postgres, MongoDB, SingleStore, and S3).
Leverage Generative AI tools for deep research, data analysis, and coding to accelerate insights.
Analyze large datasets to uncover trends, patterns, and anomalies, applying domain knowledge to interpret data and provide valuable insights for the maritime industry.
Maintain and ensure data quality and integrity, conducting thorough checks to monitor, identify, and resolve inconsistencies, and taking accountability for critical data and infrastructure.
Visualize findings, use data storytelling, and document research in technical papers and logs to understand and communicate actionable insights effectively to stakeholders.
Collaborate effectively with cross-functional teams (including domain and technical experts) to address research challenges and optimize data processes.
Join the Data Analysts technical guild to help grow data analysts professional community.