לוח משרות דרושים הייטק דאטה בפתח תקווה, לחיפוש זה נמצאו 26 משרות

our company offers hope to patients suffering from rare and severe diseases by forming partnerships with emerging biotech companies to accelerate access to highly innovative therapies in international markets. As the creator and leader of the global partnership category in the pharma industry, we strive to be Always Ahead and work relentlessly to bring therapy to patients in need, no matter where they live. Our values are at the core of every action we take, and we are committed to going above and beyond to benefit the patients we serve. We are a dynamic, fast-paced company operating in over 34 countries on 5 continents. We are looking for out-of-the-box thinkers, people who are passionate, caring, agile, and adaptive, to join us on our mission. If you are looking to make a difference in people's lives, we invite you to join us! We are looking for a motivated and business-oriented data Specialist to join our global data & BI team. In this role, you will design, develop, and maintain modern data pipelines and data solutions that support critical business processes across the organization. You will work closely with global stakeholders, integrate data from multiple sources, ensure data quality and reliability, and contribute to modern data and AI initiatives. (*Please note, the internal title for this role is Senior data & BI Specialist, Business Technology.)
Responsibilities:

* Design, build, and maintain scalable ETL /ELT pipelines
* Develop and optimize complex SQL queries and data transformation processes
* Integrate data from internal and external systems, including APIs, databases, and third-party platforms
* Own data quality, monitoring, reliability, and governance processes
* Investigate and resolve data -related issues while supporting business users
* Take ownership of data workflows from design and development through production support
* Collaborate with global stakeholders to understand business requirements, analyze data discrepancies, and deliver reliable data solutions
* Design, develop, and maintain AI-powered data solutions that support business decision-making and operational excellence
* Build and implement monitoring capabilities (e.g. anomaly detection, forecasting, etc.) using modern AI capabilities
* Partner with business teams to identify opportunities for applying AI and LLM-based solutions to real-world business challenges

As a Data Science Manager, you will lead, mentor, and grow a team of applied data scientists working on machine learning models that power AI-driven cybersecurity solutions. You will own the end-to-end development lifecycle of AI projects, from exploratory research and experimentation through to scalable deployment and optimization. In this role, you will partner with engineering and product leadership to define technical strategies, prioritize initiatives, and ensure successful model delivery. You will also drive innovation across a broad spectrum of ML domains, including supervised/unsupervised learning, anomaly detection, and generative AI, while providing hands-on guidance and championing best practices in MLOps, data governance, and model evaluation.
Key Responsibilities
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 a strong, hands-on Data Engineer to join our team and play a key role in building our data infrastructure from the ground up. In this role, you will design and implement scalable data pipelines and platforms, supporting both batch and real-time use cases. You will work closely with analysts and stakeholders to deliver reliable, high-quality data solutions, and take full ownership of data flows - from ingestion to consumption. This is a great opportunity for an executor who enjoys building, moving fast, and making an impact.
What will your job look like?
Design, build, and maintain robust and scalable data pipelines (batch and real-time) end-to-end.
Design and implement scalable, flexible data architectures to support evolving business needs.
Build and manage data platforms, including data lakes and data warehouses.
Integrate multiple data sources (structured and unstructured) into a unified data platform using batch (ETL) and real-time streaming solutions.
Design and implement efficient data models, schemas, and database structures (SQL / NoSQL).
Develop and implement data quality processes to ensure accuracy, consistency, and reliability.
Monitor, optimize, and troubleshoot data infrastructure to meet performance and SLA requirements.

We are looking for a strong, hands-on Data Platform Engineer to join our team and play a key role in building our data infrastructure from the ground up.
In this role, you will design and implement scalable data pipelines and platforms, supporting both batch and real-time use cases.
You will work closely with analysts and stakeholders to deliver reliable, high-quality data solutions, and take full ownership of data flows - from ingestion to consumption.
This is a great opportunity for an executor who enjoys building, moving fast, and making an impact.
What will your job look like?
Design, build, and maintain the underlying infrastructure for a modern cloud-based data platform.
Implement and manage CI/CD processes for data pipelines and platform deployments across development and production environments.
Design and manage secure, scalable AWS-based data infrastructure, including IAM roles, permissions, policies, networking, and environment isolation.
Build and maintain orchestration, monitoring, alerting, and observability capabilities for data pipelines and platform services.
Support deployment, reliability, and operational excellence of data workloads running on technologies such as Spark, DBT, Airflow, Athena, and AWS services.
Collaborate closely with Data Engineers, Analysts, BI teams, and IT/Cyber teams to ensure secure and scalable data operations.
Monitor, troubleshoot, and optimize platform performance, availability, and cost efficiency.
Establish best practices for infrastructure-as-code, deployment standards, security, and production readiness.

We are looking for a motivated and business-oriented Data Engineer to join our global Data & BI team.
In this role, you will design, develop, and maintain modern data pipelines and data solutions that support critical business processes across the organization.
You will work closely with global stakeholders, integrate data from multiple sources, ensure data quality and reliability, and contribute to modern data and AI initiatives.
(*Please note, the internal title for this role is Senior Data & BI Specialist, Business Technology.)
Responsibilities
Design, build, and maintain scalable ETL/ELT pipelines
Develop and optimize complex SQL queries and data transformation processes
Integrate data from internal and external systems, including APIs, databases, and third-party platforms
Own data quality, monitoring, reliability, and governance processes
Investigate and resolve data-related issues while supporting business users
Take ownership of data workflows from design and development through production support
Collaborate with global stakeholders to understand business requirements, analyze data discrepancies, and deliver reliable data solutions
Design, develop, and maintain AI-powered data solutions that support business decision-making and operational excellence
Build and implement monitoring capabilities (e.g. anomaly detection, forecasting, etc.) using modern AI capabilities
Partner with business teams to identify opportunities for applying AI and LLM-based solutions to real-world business challenges
Develop and operationalize AI workflows and data products from proof-of-concept through production deployment.

We're looking for a Data Scientist to turn our network data into a competitive advantage. You'll work directly with terabytes of telecom signaling, session, and usage data to build models that improve network selection, detect anomalies, optimize cost-per-gigabyte, and surface insights that shape product and commercial strategy. This is a high-impact role sitting at the intersection of ML, telecom engineering, and business decision-making.

What You'll Do

Design and deploy machine learning models on network data - including network selection optimization, churn and usage prediction, fraud and anomaly detection, and QoS/QoE forecasting.

Analyze CDRs, signaling events (Diameter, GTP, SIP), session logs, and radio-level metrics to identify performance issues, cost drivers, and growth opportunities.

Partner with the Network Operations and Product teams to translate raw telemetry into actionable signals - e.g., which carrier to steer traffic to in a given country at a given hour.

Build forecasting and segmentation models that inform pricing, capacity planning, and customer lifecycle strategy.

Own analyses end-to-end: framing the business question, exploring the data, building the model, validating it, and communicating findings to both technical and executive audiences.

Define and track KPIs for network quality, customer experience, and commercial performance, and build dashboards that make those metrics visible across the company.

Mentor junior data scientists and analysts, and help raise the bar on data science practices, code quality, and experimentation rigor.

A True Problem Solver Were looking for a Senior DS who thrives on End-to-End ownership. You aren't just given a dataset; you identify the business opportunity, architect the mathematical solution, and write the high-quality, production-ready code that brings it to life. This is the ultimate "DS Candy Store" for those who love research but live for the adrenaline of seeing their code drive real revenue.
What Youll Do:
End-to-End Ownership: Own the entire lifecycle: from defining the business problem and KPI to deploying and monitoring the solution in production
High-Scale Architecture: Design and implement ML models & handling high-cardinality data at massive scale
Engineering Excellence: Write clean, modular, and scalable code. We believe great Data Science is built on a foundation of great Software Engineering
Strategic Leadership: Mentor the team through complex technical hurdles and contribute directly to our algorithmic roadmap

We are responsible for building data pipelines end to end-from raw data ingestion to the creation of actionable datasets-following the bronze, silver, and gold paradigm. This includes business logic, infrastructure, ETLs, optimization, and ongoing maintenance.

The data we deliver drives insights and decision-making across the organization and enhances our product offerings. We leverage technologies such as AWS, Snowflake, Iceberg, Airflow, Spark, and more.

What Youll Do
Lead the translation of business and product requirements into scalable data models, transformations, and pipelines.

Design and own datasets across bronze, silver, and gold layers, including defining grain, aggregations, and data contracts.

Develop and maintain SQL-heavy data pipelines and Airflow DAGs (workflow logic, dependencies, backfills, python, and lots of SQL).

Own data correctness for key business metrics (e.g., ARR), including deep root cause analysis and resolution of data issues.

Define and drive best practices for SQL, data modeling, and pipeline design across the team.

Optimize queries and data models for performance, scalability, and cost efficiency.

Collaborate closely with product managers, analysts, and BI developers to refine requirements and ensure high-quality data delivery.

Develop AI-agents to accelerate data analysis by internal and external users.

Work with complex data inputs (e.g., JSON, schemas, logs) and incorporate them into robust data pipelines.

A growing B2B SaaS company is looking for an experienced Head of Data Science to lead its Data Science function and drive the next generation of AI and machine learning capabilities.

This is a strategic leadership role combining people management, hands-on problem-solving, cross-functional collaboration, and ownership of data-driven innovation across the organization.


Responsibilities:

Lead and mentor a global team of Data Scientists.

Define and execute the company's Data Science strategy.

Drive the development of advanced machine learning, optimization, and forecasting solutions.

Partner closely with Product, Engineering, Customer Success, and executive leadership.

Translate complex business challenges into scalable analytical solutions.

Support customer-facing initiatives and strategic engagements when needed.

Establish best practices for experimentation, model evaluation, and performance measurement

Act as a key stakeholder in shaping the company's AI vision and roadmap