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לפני 2 שעות
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
Our great team is expanding and looking for a 2 Yeare experienced data Scientist who
Own data projects end to end: Research, POCs, deployment, monitoring, and maintenance

Develop, TEST, and deploy ML models with a focus on time series forecasting and predictive analytics

Research and build LLM-powered applications using text embeddings, RAG, and prompt engineering

Build robust data pipelines for structured and unstructured data

Establish and run A/B testing frameworks to support data -driven decisions

Partner with product, engineering, and business teams to present findings clearly
Requirements:
Own the full project lifecycle end to end, from business needs to research questions and POCs, through development, deployment, monitoring, and maintenance
Develop, TEST, and deploy Machine Learning models with a focus on time series forecasting and predictive analytics
Research and build LLM-powered applications for personalization, recommendation systems, and internal productivity tools
Work with text embeddings, feature engineering, and RAG architectures
Refine prompts and evaluate LLM performance to ensure accuracy, safety, and consistency
Build robust data pipelines for structured and unstructured data
Establish and run A/B testing frameworks to support data -driven decisions
Partner with product, engineering, and business teams to present findings clearly and drive action
This position is open to all candidates.
 
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לפני 21 שעות
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for a Senior Data Science who is excited about designing and building production-grade AI systems powered by modern LLMs and machine learning.

This role is ideal for someone who enjoys working at the intersection of AI, engineering, and product, and who is passionate about turning cutting-edge AI capabilities into reliable, scalable systems that solve real customer problems.

Youll work closely with product managers, data scientists, and engineers to design, build, and deploy AI-powered solutions - including LLM pipelines, agents, and intelligent automation systems that power our core products.

This is a hands-on role where youll take ownership of the full lifecycle of AI features - from problem framing and architecture design to deployment, evaluation, and iteration in production.

Responsibilities
Design and build AI-powered systems that leverage LLMs, embeddings, and modern NLP techniques to transform raw product data into structured, actionable insights.
Develop and maintain production-grade AI pipelines including prompt workflows, agents, retrieval systems (RAG), and automated decision processes.
Work closely with product and engineering teams to translate business needs into scalable AI solutions.
Architect systems that combine LLMs, data pipelines, and traditional ML into robust end-to-end products.
Experiment with and integrate new AI tools, models, and frameworks to continuously improve system capabilities and performance.
Own the full lifecycle of AI features - from design and prototyping to deployment, monitoring, and iteration.
Ensure reliability and performance of AI systems in production, including evaluation frameworks, guardrails, and monitoring.
Collaborate across teams to define best practices for AI system design, prompt engineering, and agent orchestration.
Collaborate closely with cross-functional team members, effectively communicate complex ideas, share knowledge, and mentor engineers and data scientists to elevate team standards and impact.
Requirements:
6+ years of experience in software engineering, machine learning, data science, or related technical roles.
3+ years of hands-on experience building machine learning or AI systems in production.
Strong experience working with textual data and NLP techniques such as embeddings, classification, semantic search, or information extraction.
Hands-on experience building applications powered by LLMs (e.g., prompt pipelines, RAG systems, agents, or structured extraction).
Comfortable leveraging AI-powered developer tools (e.g., Cursor, Claude Code, Copilot, ChatGPT) to accelerate development and experimentation.
Strong product intuition - you focus on solving real user problems, not just building models.
Excellent collaboration and communication skills.
Degree in Computer Science, Engineering, or a related technical field - or equivalent practical experience.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a talented and experienced Data Scientist to join our Research Data Science team and play a key role in shaping the future of cloud-native network security. Your primary mission will be to lead the development and deployment of AI-driven capabilities that protect enterprise networks at scale through our companys SASE platform, powering core products such as our AI assitant, DLP, XDR, IPS, and more.
Leveraging rich, real-time data from our global backbone and Cloud data warehouse, you will apply advanced reserach analytics, machine learning, deep learning and GenAI techniques to solve complex cybersecurity and networking challenges.
This is an exciting opportunity to join a fast-growing company and drive innovation in the rapidly evolving SASE space.
Key Responsibilities
Lead the design, development, and deployment of AI/ML models that enhance our companys security and networking products
Leading networking and security research, including analysis of large-scale network traffic and security data to identify patterns, threats, and opportunities for product improvement
Research, fine-tune, and train models optimized for real-time inline inference under limited compute resources
Collaborate cross-functionally with product, engineering, and support teams to translate product and business needs into AI solutions
Define and track success metrics to ensure AI solutions meet performance and business goals.
Requirements:
Minimum 3 years of professional experience in Data Science roles
Hands-on experience in networking and/or cybersecurity domains
Proven experience building and deploying LLM-based applications and agents (e.g., RAG pipelines, tool-use agents, prompt engineering at scale)
Strong foundation in classical machine learning methods (supervised, unsupervised learning, clustering)
Practical experience with deep learning frameworks such as TensorFlow or PyTorch, including NLP techniques
Proven experience deploying models on cloud platforms like AWS, Azure, or Google Cloud
Excellent analytical, problem-solving, and communication skills
Self-motivated, collaborative, and able to work independently
How to Stand Out
Experience with real-time or low-latency AI inference in production environments.
Advanced degree (MSc or PhD) in Computer Science, Statistics, Mathematics, or a related quantitative field.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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4 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: More than one
we are looking for a Junior Fraud Data Scientist.
As a Junior Fraud Data Scientist, you will contribute to our ongoing efforts to protect our ecosystem from financial threats and abuse. Working under the guidance of senior team members in a data-rich environment, you will assist in identifying malicious behaviors, support detection coverage, and help maintain our automated mitigation strategies.
This role is designed for an analytical professional with 1-2 years of experience who wants to build a deep expertise in adversarial data, learn from an experienced team, and develop their technical skills across modern cloud data platforms.
What You Will Be Doing
Exploratory Data Analysis: Support the team by mining behavioral and transactional datasets to help identify anomalies and emerging fraud patterns.
Model Support & Optimization: Assist in building, tuning, and validating machine learning models (e.g., XGBoost, LightGBM) under the supervision of senior data scientists.
Feature Generation: Extract, engineer, and prepare new data features from structured and unstructured sources to help improve model performance.
Dashboarding & Monitoring: Build and maintain internal dashboards and pipelines to track model health, data drift, and key fraud KPIs.
Cross-functional Collaboration: Work alongside Fraud Analytics and Product teams to help translate operational fraud insights into automated data solutions.
Requirements:
Experience: 1-2 years of hands-on professional experience as a Data Scientist or Data Analyst in a data-intensive environment.
Data Science Tech Stack: Solid proficiency in Python (Pandas, NumPy, Scikit-Learn) and strong capability writing and optimizing SQL queries.
Modern Data Infrastructure: Exposure to or basic hands-on experience working within environments like Databricks and data warehouses like BigQuery.
Academic Background: Degree in a quantitative field (Computer Science, Statistics, Data Science, Industrial Engineering, or equivalent).
Business-Impact Focus: An understanding of how to look past raw model metrics (precision/recall) to appreciate the operational impact of data decisions.
Communication: Fluent English with the ability to communicate technical findings clearly to team members.
Bonus Points
Prior exposure to or hands-on projects involving machine learning models in a live, real-time production environment.
Familiarity with MLOps or orchestration tools such as MLflow or Airflow.
Previous domain exposure in FinTech, e-commerce, payments, or trust & safety.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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עדכון קורות החיים לפני שליחה
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Location: Tel Aviv-Yafo
Job Type: Full Time
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.
Requirements:
Qualifications & Skills:

MSc or PhD (or equivalent experience) in a quantitative field such as Computer Science, Statistics, Economics, Operations Research, Mathematics, Engineering, Artificial Intelligence, or Physics.

Relevant professional or academic experience applying Machine Learning to business problems (typically MSc + 5 years, or PhD + 3 years).

Proven track record designing and executing end-to-end research and development projects, and generating measurable impact through large-scale ML model development. Evidence such as peer-reviewed publications, patents, or open-source contributions is a plus.

Advanced knowledge and experience in Causal Inference, Uplift Modeling, Reinforcement Learning, Active Learning, and/or Optimization.

Strong proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, XGBoost).

Experience working with large-scale data systems and production ML pipelines.

Solid understanding of data analytics, A/B testing, and statistical experimentation.

Experience with distributed computing and data technologies such as Spark, Hadoop, Kafka, and SQL.

Familiarity with version control systems and software engineering best practices.

Experience collaborating cross-functionally with developers, analysts, product managers, and UX specialists to deliver machine learning-driven products.

Ability to communicate complex scientific and technical ideas clearly and effectively to both technical and non-technical audiences.

Excellent English communication skills, both written and verbal.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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4 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
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
Requirements:
MSc in Computer Science, Mathematics, Engineering, or equivalent experience
Strong NLP expertise - Must
Deep understanding of modern NLP methods (transformers, LLMs, embeddings, etc.)
Proven experience delivering NLP solutions to production
Leadership experience - Must
2+ years of experience managing or leading data science / ML teams
Demonstrated ability to mentor and grow team members
Hands-on ML/NLP experience - Must
5+ years of experience in research and implementation of ML-based solutions
Strong coding skills (Python - must; Java/C#/Scala - advantage)
Production experience - Must
Experience deploying and maintaining ML/NLP systems in production environments
Familiarity with scalable systems and data pipelines
LLM + Deep Learning experience - Must
Experience working and training LLMs, and deploying them at large-scale
Experience with modern DL frameworks (PyTorch, TensorFlow)
Strong problem-solving and critical thinking skills
Excellent communication skills
Ability to communicate complex ideas to both technical and non-technical stakeholders
Nice to Have:
Experience in e-commerce or recommendation systems
Experience with experimentation, A/B testing, and product impact measurement
Background in leading cross-team or cross-domain initiatives
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8739937
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4 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
we are looking for a Fraud Data Scientist.
As a Fraud Data Scientist, you will be at the front lines of protecting our ecosystem from sophisticated financial fraud and abuse. You will join a high-impact team operating in a data-rich, high-frequency environment where seconds matter.
In this role, you will take ownership of the end-to-end machine learning lifecycle-from uncovering complex fraud patterns to deploying highly scalable, real-time models into production. You will collaborate closely with Engineering, Product, and Risk Operations to build robust defenses that balance strict security with a seamless user experience.
What You Will Be Doing
Model Development & Deployment: Design, train, and deploy advanced machine learning models (e.g., gradient boosting, anomaly detection, graph networks) to detect and mitigate fraud in real-time.
Production Ownership: Take full ownership of putting models into production systems, ensuring low-latency execution and high reliability.
Agentic Workflows: Research, build, and implement Agentic flows and LLM-driven orchestration to automate multi-step fraud decisioning, logic routing, and investigation paths.
Adversarial Analysis: Conduct deep-dive exploratory analysis on massive datasets to identify emerging fraud vectors, loops, and coordinated attacks.
Feature Engineering: Build and optimize real-time streaming and batch features to improve model signal and precision.
Experimentation & Monitoring: Design rigorous shadow-testing and A/B testing frameworks for new models. Set up continuous monitoring pipelines to catch data drift and performance degradation early.
Requirements:
Experience: Minimum of 3+ years of applied Data Science experience with a proven track record across fintech domains, with experience in fraud, risk, or payments preferred.
Production Expertise: Proven, hands-on experience deploying and maintaining machine learning models in high-traffic production environments is required, with real-time experience preferred.
Data Science Tech Stack: Expert-level Python programming (Pandas, NumPy, Scikit-Learn, XGBoost/LightGBM) and exceptional SQL skills for querying massive, complex datasets.
Data Environment: Robust experience working within cloud data environments like Databricks, and querying/manipulating large-scale datasets in data warehouses like BigQuery.
Orchestration & MLOps: Practical experience with machine learning lifecycle and orchestration tools, such as MLflow and Airflow.
Business-Impact Focus: A strong ability to translate raw model results into real-world business outcomes. You know how to balance technical model performance (precision/recall) with financial impact, operational realities, and the user experience.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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עדכון קורות החיים לפני שליחה
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4 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for a Data scientist Expert to join us and spread our power. As a Data Scientist you will be responsible for driving research and development of autonomous AI agents and LLM-powered systems. 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 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.
Requirements:
WHAT YOULL BRING
An M.S. or Ph.D. degree in computer science, statistics, or related field OR equivalent work experience
5+ years of experience in leading data science and machine learning projects, with significant hands-on work building LLM-based applications or AI agents
Deep practical experience with LLMs - prompt engineering, fine-tuning, model selection, and understanding trade-offs across providers and model families
Experience with distributed cloud systems - hands-on familiarity with cloud-native architectures at scale
Strong knowledge of deep learning models and common model architecture such as transformer models
Knowledge of programming languages that are used in AI research, such as Python, and experience with AI frameworks (e.g., Hugging Face, LangChain, OpenAI, scikit-learn, TensorFlow, PyTorch)
Ability to work independently in a fast-paced, and come up with creative solutions to challenging problems
Excellent communication (both written and verbal) and presentation skills
Advantage: Knowledge of cybersecurity principles, attack vectors, and defense mechanisms.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
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Location: Tel Aviv-Yafo
Job Type: Full Time
We're looking for a Senior Car Insurance Pricing Expert to help shape how we price risk across our global business, from our Tel Aviv office.
This isn't a traditional actuarial role. You'll sit at the intersection of Insurance, Data Science, Product, Engineering, and Business Strategy on our Insurance team, owning hard pricing and risk-management problems end to end. That means finding opportunities, designing better approaches, building scalable tools with technical teams, and turning insights into decisions that move growth, profitability, and risk selection forward.
You might be a trained actuary, a pricing leader, a decision scientist, or a technically strong insurance operator who's built serious pricing capabilities. Formal credentials are a plus, but they're not the point. The point is whether you can use data, insurance intuition, statistical rigor, and AI-enabled tools to solve complex pricing problems better and faster than the industry standard.
We believe three things matter for every role : drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll
Own and evolve core components of Car pricing strategy, bringing analytical rigor and product-minded creativity to how we price risk
Identify high-leverage opportunities across rating, underwriting, segmentation, risk selection, growth, profitability, and portfolio management
Build, evaluate, and improve Car pricing and risk models using actuarial methods, machine learning, AI-enabled workflows, and strong business judgment
Partner with Data Science, Product, Engineering, Finance, and Growth to turn pricing ideas into scalable capabilities
Translate complex pricing problems into clear product and platform requirements, helping teams build internal tools that make better decisions faster
Define and track key metrics - loss ratio, rate adequacy, conversion, retention, segmentation lift, and model performance - to keep decisions grounded in real impact
Make complex actuarial and pricing concepts clear and actionable for technical and non-technical audiences alike, and help build pricing acumen across the Tel Aviv team
Requirements:
8+ years of experience in Car insurance pricing, actuarial science, decision science, risk analytics, or a closely related field
A proven track record solving complex pricing, underwriting, segmentation, or risk-management problems with measurable business impact
Strong analytical instincts - knowing how to find signal in data, make decisions under uncertainty, and separate elegant analysis from useful analysis
Hands-on fluency with modern analytical tools, agentic AI capabilities, and code - including experience using generative AI, coding agents, or advanced automation to materially improve analytical workflows
Solid understanding of Car insurance pricing fundamentals, including rating plans, loss costs, rate adequacy, segmentation, model validation, telematics and financial performance.
Familiarity with predictive modeling methods such as GLMs, gradient boosting, random forests, clustering, and feature engineering
Experience building or modernizing pricing platforms, rating engines, underwriting tools, or internal decision-support software
Product-minded problem solving: the ability to turn a messy workflow, technical constraint, or business problem into a clear, prioritized path forward - with a track record of partnering with Product and Engineering teams to ship production-grade tools
Strong communication skills - you can explain pricing decisions, tradeoffs, and model outputs clearly to executives, engineers, product teams, and regulators
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are seeking a Senior Data Scientist to join the team that builds the predictive intelligence powering the app. You will own the ML models behind user engagement, cardiovascular risk stratification, and personalized health recommendations - the systems that determine what users see, when they're nudged, and how their health trajectories are shaped.

This role demands both statistical depth and engineering proficiency - you will be expected to take models from research through to deployment, write code built for production, and use AI coding assistants fluently as part of how you get work done.

Responsibilities
Lead end-to-end development of predictive ML models. From data exploration and feature engineering through training, validation, deployment, and ongoing monitoring across engagement and clinical risk domains.
Apply strong statistical foundations to model design, feature selection, uncertainty quantification, and interpretation of results
Write production-grade Python code that is clean, tested, and built for maintainability and scale.
Use AI coding assistants to accelerate development, code review, and documentation without sacrificing quality or rigor.
Partner with product managers, data engineers, and software engineers to translate strategic questions and user behavior patterns into measurable, data-driven solutions.
Research and implement cutting-edge ML techniques spanning supervised and unsupervised learning, causal inference, deep learning, and reinforcement learning to tackle complex healthcare challenges.
Contribute to MLOps infrastructure: model serving, versioning, evaluation pipelines, and monitoring.
Design and interpret A/B tests and other experimental methodologies to measure the impact of models, features, and interventions.
Requirements:
Qualifications:
5+ years of hands-on experience developing, deploying, and maintaining ML models in production environments.
Bachelor's degree in Statistics, Computer Science, Applied Mathematics, Engineering, or a related quantitative field - a strong statistical foundation is essential for this role.
Deep expertise in statistics and probability: distributions, inference, hypothesis testing, Bayesian methods, causal inference, and experimental design, with the ability to apply these rigorously in a healthcare context.
Strong software engineering skills in Python: production-grade practices, version control, testing, and reproducibility.
Proficiency using AI coding assistants as a core part of the development workflow.
Expertise with ML frameworks such as PyTorch, scikit-learn, XGBoost, or LightGBM.
Experience building or working within ML pipelines end-to-end, including feature engineering, model registries, and deployment tooling.
Strong ability to translate complex statistical and technical findings into clear insights and recommendations for both technical and non-technical stakeholders.

Advantage:
Experience with cloud platforms (AWS preferred), containerization (Docker, Kubernetes), and MLOps platforms.
Prior work with healthcare or clinical datasets, including wearable device data, EMR, or claims data.
Experience with recommendation systems, reinforcement learning, or advanced causal inference.
This position is open to all candidates.
 
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21/06/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for a sharp and driven Product Data Scientist to join our fast - paced Data Labs team. As part of a high-performing group of analysts, youll handle complex, custom requests from some of the biggest names in the market, turning raw data into strategic, ad hoc insights. The work is intense and constantly evolving - it requires strong analytical skills and the ability to work independently under pressure. Youll need to be curious, adaptable, and willing to dive deep to find answers where others might stop. If you thrive in a demanding environment and are excited by the opportunity to make a real impact, we want you on our team.
What does the day to day of a Product Data Science Customer Facing (Data Labs) look like:
Building custom-made reports end to end - from meeting with the client and understanding their needs, to writing the code and setting up the report for ongoing delivery.
Apply your expertise in quantitative analysis and data mining to turn data into insights.
Conduct research and develop tools which will help answer client's business. questions by using our raw data sets and algorithms.
Partner with Engineering teams to establish an infrastructure to scale solutions.
Partner with Advisory Services team of Consultants to answer strategic business questions and deliver custom data products seamlessly.
Requirements:
Bachelors degree in Computer Science, Engineering, Statistics, Mathematics, or a related quantitative field (or equivalent practical experience).
3+ years of experience as a Product Data Scientist, Solutions Engineer, or in a similar analytical role.
Strong proficiency in SQL and Python.
Demonstrated experience solving complex analytical problems using quantitative and statistical approaches.
Experience working in customer-facing environments, including:
Collaborating with a wide range of stakeholders - including Engineers, Sales, and customer-facing teams - to scope problems, align on requirements, and deliver data-driven- solutions that meet customer and business needs.
Proven experience owning enterprise customer engagements end to end, including feasibility evaluation, solution design, implementation, and ongoing delivery of data-driven insights.
Excellent communication skills in English, with the ability to present insights clearly and influence both technical and non-technical audiences.
Proven ability to independently lead and own analytical initiatives end to end in ambiguous, fast-paced environments.
Master's Degree in a quantitative field - Big Advantage.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8703322
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