דרושים » תוכנה » AI Data Quality Analyst (Paradox)

As our Product Analyst, you will play a key role in translating complex behavioral, marketing, and platform data into clear business insights that drive product strategy, customer value, and commercial decision-making. This is not a passive reporting role. We are looking for someone proactive, curious, and business-oriented - someone who can identify the right questions, investigate complex datasets, uncover meaningful patterns, and turn findings into actionable recommendations for Product, R&D, Customer Success, Sales, and leadership teams. platform processes large-scale consumer journey data to help global brands and publishers understand influence, attribution, and performance in a clickless discovery environment. As our products become more sophisticated, we need a strong analytical partner who can connect data, product logic, customer needs, and business context into one clear story. You will help define what success looks like, measure product performance, validate new capabilities, support strategic customer and partner initiatives, and ensure our teams make decisions based on strong data foundations.

What You Will Do

Translate complex data queries into clear business insights, recommendations, and product decisions.
Analyze large-scale behavioral, marketing, attribution, and product datasets to identify trends, risks, opportunities, and anomalies.
Partner with Product, R&D, CS, Sales, and leadership to frame business questions and define the right analytical approach.
Define KPIs, success metrics, dashboards, and analytical frameworks for new and 2 existing products.
Support product strategy by measuring adoption, feature performance, customer impact, and revenue opportunities.
Analyze clickless discovery, publisher influence, advertiser performance, share of voice, and conversion behavior.
Identify data inconsistencies, gaps, and edge cases, and partner with Data and Engineering to improve trust in our insights.
Present clear narratives and stakeholder-ready materials that connect data findings to business impact.
Your Day-to-Day Work

Write advanced SQL queries across large analytical datasets.
Use Python, Pandas, notebooks, and analytical workflows to investigate complex data
Build dashboards and reports in BI tools platforms for data visualization
Run deep-dive investigations into product usage, customer behavior, performance trends, and data anomalies.
Work with Product Managers on discovery, feature definition, rollout measurement, and post-launch analysis.
Collaborate with Data and Engineering teams on table logic, metric definitions, tracking requirements, and validation.
Prepare executive summaries, customer-facing insights, sales enablement analyses, and internal decision materials.
Proactively identify new insights, risks, and opportunities beyond the original request.

we are seeking a Senior Data Analyst position to join the BI Team, with a passion for technology, to solve unique problems within our measurements. Our team solves many challenges in turning raw data into accurate signals and extracting insights to improve the 365Scores products. Appropriate candidates have an understanding of multiple components across the big data stack: large-scale data analysis, data quality, statistics, and visualization. If you are the kind of researcher who's focused on results and a quick learner, this role is for you. This position is located in our Tel Aviv office.

Responsibilities
Function as the data authority in the Monetization domain - performing ad-hoc research and analysis on the company's rich data to support unique and strategic business questions.
Define, analyze, and monitor KPIs and OKR metrics to continually improve company products.
Analyze large, complex data sets to address strategic and operational business questions.
Actively take part in building and maintaining our AI Driven-BI Agentic Architecture.
Build dashboards and visualizations to answer key questions for the company's in-house various teams, specifically for the Monetization Team.
Perform qualitative, quantitative, and statistical analysis.
True passion for understanding data and finding Insights.
Provide actionable recommendations and conclusions from data to shape features and future product road maps.

As Head of Analytics, youll lead the analytics team and strengthen how data is used to support decision-making across the company. Reporting to the VP of Data & Analytics, youll translate the broader data strategy into clear priorities, high-quality analytical delivery, and measurable business impact.

Youll manage and develop teams of analysts and BI, partner closely with senior stakeholders across Product, Sales, Marketing, Finance, Customer Success, and Operations, and ensure that the company has trusted metrics, actionable insights, and scalable analytical capabilities.

This is a strategic and hands-on leadership role. Youll be expected to set direction, create structure, raise analytical standards, and remain closely involved in the companys most important business questions.

Youre welcome to work in our offices in Tel Aviv, Israel

Your responsibilities will include:

Team leadership and development. Lead, mentor, and develop the analytics team. Set clear expectations, establish ownership, support professional growth, and create a high-performance culture focused on business impact, analytical quality, and accountability.
Analytics strategy execution. Partner with the VP of Data & Analytics to shape the analytics strategy and own its execution, prioritization, and delivery. Translate company goals into a clear analytics roadmap and ensure resources are focused on the highest-impact business needs.
Business partnership. Act as a trusted analytical partner to senior leaders across Product, Sales, Marketing, Finance, Customer Success, and Operations. Understand their objectives, challenge assumptions, and help turn strategic questions into measurable decisions and actions.
Decision support and advanced analysis. Lead high-impact analyses across customer behavior, product performance, revenue, retention, pipeline, operational efficiency, and business growth. Ensure findings are translated into clear recommendations rather than presented as data alone.
Metrics and analytical governance. Establish and maintain consistent KPI definitions, business logic, and analytical standards. Ensure stakeholders use trusted and aligned metrics across dashboards, reports, forecasts, and business reviews.
Dashboard and reporting oversight. Guide the design, implementation, and improvement of executive and operational dashboards. Ensure reporting is relevant, reliable, easy to use, and aligned with business priorities.
Self-service analytics. Enable business teams to access and use data independently while maintaining appropriate governance, security, quality, and consistency. Identify where self-service creates value and where centralized analytical support is required.
AI-driven analytics. Help define and implement AI-assisted analytics capabilities that reduce manual reporting, accelerate insight generation, support natural-language access to data, and proactively surface risks or anomalies. Establish clear quality and validation standards for AI-generated outputs.
Cross-functional data collaboration. Work closely with Data Engineering, Data Architecture, and other technical teams to ensure that analytical datasets, semantic models, and data pipelines support current and future business requirements.
Operating model and prioritization. Build scalable processes for intake, prioritization, delivery, documentation, and stakeholder communication. Balance urgent business requests with strategic initiatives and long-term capability development.

We are looking for a Senior AI Engineer to design and build production-grade, LLM-powered systems. You'll work at the intersection of software engineering and applied AI - shipping agents, RAG pipelines, and tool-using systems that solve real problems at scale. This is a hands-on, high-ownership role for someone who thrives at the frontier of what's possible with modern LLMs and isn't afraid to write the glue, the infrastructure, and the prompts that make it all work.
This is a **cross-functional, company-wide role**. You won't be embedded in a single product team - instead, you'll partner with every department to identify high-leverage opportunities and build AI-powered tools and workflows that boost productivity and efficiency across the entire organization.
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
What You'll Do:
- Design, build, and operate LLM-powered applications, agents, and workflows end-to-end - from prototype to production.
- Architect retrieval, context engineering, and tool-use strategies that make models reliable, accurate, and cost-efficient.
- Integrate LLMs with internal services, third-party APIs, and data stores to automate complex business and engineering workflows.
- Build, evaluate, and continuously improve evaluation harnesses for non-deterministic systems.
- Collaborate closely with product, research, and platform teams to translate ambiguous problems into shipped capabilities.
- Stay ahead of the rapidly evolving LLM ecosystem (models, frameworks, agentic patterns) and bring the best ideas into our stack.

Prisma Photonics is a rapidly growing startup company, developing the next-generation smart-infrastructure solutions based on novel fiber-sensing technology. The company offers an award-winning disruptive solution: a “sensor free” approach to smart infrastructure. The company is VC backed and in the revenues stage. Combining pioneering technology in optical fiber sensing with state-of-the-art AI, we help protect human lives and keep critical energy. We're seeking a Senior Data Analyst to take a key role in unlocking the value of our vast datasets collected over years and across a diverse client base. In this role you’ll dive deep into data related to power line capacity, macro-scale and micro-scale weather, grid resilience, conductors and more. Your work will directly influence how we optimize grid performance and respond to the challenges of today’s energy landscape. This role requires a combination of technical skills, analytical thinking, and business acumen. The ideal candidate is highly skilled in data analysis techniques and tools and has a strong ability to translate data insights into actionable recommendations. You’ll thrive here if you enjoy blending technical expertise, critical thinking, and business understanding to drive smarter, data-informed decisions.

What You’ll Do:

* Collect and integrate data from various sources, including fiber-based data, weather stations, line sensors, and SCADA systems.
* Be a part of the product management team - explore customer needs, define data products and processes, and align outputs of the data science team with the company roadmap.
* Ensure data quality and consistency for accurate analysis and reporting.
* Conduct statistical analysis and use data visualization tools to present findings.
* Monitor and evaluate the performance of Dynamic Line Rating (DLR) systems and grid resilience detectors and identify opportunities for improvement.
* Provide data-driven insights and recommendations to support decision-making processes.
* Interpret and communicate results to customers and management in a clear and concise manner.
* Present key findings of your analysis to customers around the globe.

What You Bring:

* B.Sc. degree in a related field. (M.Sc./Ph.D. is an advantage)
* Experience with AI-native development environments and automation with coding agents.
* At least 5 years of experience in data analysis, business intelligence, or a related field.
* Proficiency in data analysis tools such as SQL, Python (Pandas, Jupyter, Plotly).
* Experience with product management skills, driving data science and data engineering teams, experience with open ended data tasks and explorations.
* Knowledge of statistical analysis techniques and methodologies.
* Familiarity with database management systems and data warehousing.
* Strong data visualization and presentation skills in English (foreign customers).
* Experience with data visualization tools like Tableau, Power BI, Grafana, Python Plotly or similar.
* Excellent communication and teamwork skills.
* A curious mindset and a passion for solving complex problems.

We are seeking an experienced sharp and dynamic analytical mind to join our Product Analytics team as a Strategic product analyst. This position is ideally suited for those who are naturally passionate about learning, gaining knowledge, and analyzing anything they do and see with experience in utilizing data to make a significant impact.
The role requires a combination of analytical, technical, problem-solving, communication, and project management skills, and it involves working closely with various stakeholders and customers - including Product Managers, Customer Success Managers, Operations teams, Data Engineers, UI/UX Designers, SW developers, and AI experts at all levels.
Responsibilities:
As a Strategic product analyst at Aidocs Analytics group, you will play a critical role in expanding our data-driven vision and building analytics capabilities that create value for both our customers and internal teams. Your work will include:
Building scalable customer-facing analytics and data-sharing products, transforming complex data and customer needs into reliable, intuitive, and standardized solutions.
Partnering with Customer Success and Product teams to understand how customers use our products, identify opportunities to improve adoption and demonstrate value, and translate site needs into scalable analytical solutions.
Leading strategic analyses across products, workflows, and clinical domains, connecting data from multiple parts of Aidocs ecosystem to uncover insights and support business and product decisions.
Designing product KPIs and measurement frameworks, monitoring trends, and working with key stakeholders to translate findings into actionable insights.
Conducting decision-support analyses for Product, Customer Success, development, and operational initiatives.
Designing and improving scalable data models and analytics infrastructure that support customer-facing products, internal analytics, and repeatable analytical capabilities.
Continuously expanding our analytics knowledge base, improving data quality and reliability, and documenting learnings to strengthen the teams collective expertise.

We are constantly striving to make our systems reliable, scalable, and simple to operate so our services are available to travelers when they need them most. With our continued growth, we have exciting challenges ahead and we're looking for a Senior Site Reliability Engineer to join our team in Tel Aviv. This role blends classic SRE ownership with pragmatic AI SRE work: you will build and operate the platforms, automation, observability, and incident response practices that keep Navan reliable, while helping teams use AI solutions, AI providers, and their APIs safely and dependably.



This is a hands-on engineering role, not a research role. You will partner with product, platform, data, security, support, and incident response teams to make production systems and AI-powered experiences more resilient. You will use software engineering, infrastructure as code, SLOs, telemetry, provider observability, and automation as your main tools, and you will apply AI where it creates measurable reliability value rather than novelty.



This position is based out of our new Tel Aviv office.



What You'll Do:

Support AI-based application solutions where reliability matters. Partner with the development teams building AI-powered travel experiences to support the development and production operation of their solution.
Work with AI solutions, providers, and APIs. Partner with teams integrating AI capabilities and providers, with attention to API reliability, authentication, quotas, rate limits, latency and provider-specific operational constraints.
Troubleshoot AI tools and provider issues. Diagnose failures across AI-powered workflows, provider APIs, configuration, permission errors, degraded responses and related areas.
Operate reliable production platforms. implement and run cloud infrastructure,and help product teams move quickly without compromising reliability.
Improve observability. Build dashboards, alerts, traces, logs, and runbooks that make service health clear, actionable, and tied to SLOs and customer impact.
Apply AI to SRE workflows. Prototype and productionize AI-assisted systems that create effective and efficient operations
Automate operational toil. Create tools, workflows, and automation that remove repetitive manual work and make operational knowledge easier to use.

We are looking for an experienced Analytics Engineer to join our Clinical Value team and develop the data foundations, infrastructure, and analytical tools that enable our work.
This hybrid role combines Analytics Engineering with hands-on data analysis. You will translate complex analytical and clinical needs into scalable, reliable, and reusable data solutions.
You will design data models, pipelines, analytical layers, and tools that enable complex Clinical Value studies across products and customers, while remaining hands-on with selected analytical projects.
You are expected to be independent, proactive, and impact-oriented, taking end-to-end ownership of technical challenges and opportunities for improvement.
evaluation.
Responsibilities:
Design, build, and maintain the data infrastructure supporting Clinical Value analyses, including reusable data models, pipelines, analytical layers, and tools.
Own the technical and analytical implementation of complex Clinical Value applications, adapting established methodologies to different products, customers, and real-world data environments.
Develop complex analytical solutions into reusable and scalable frameworks, enabling broader and more efficient execution across the team.
Identify data-quality issues, technical bottlenecks, and repetitive processes, and develop solutions and automation to improve reliability and efficiency.
Work closely with analysts, Data Engineering, and other technical teams to translate analytical needs into effective, maintainable data solutions and establish best practices.
Lead selected hands-on data-analysis projects, analyzing complex clinical and operational datasets to generate credible, actionable conclusions.
Collaborate with Go-to-Market teams, including Customer Success, to understand customer needs and support impactful customer-facing value demonstrations.