- Location
- Tel Aviv · Tel Aviv District, Israel
- Workplace
- Onsite
- Department
- R&D
- Experience
- 3+ years
- Source
- Greenhouse
Description
About Us
Beamup helps enterprises move beyond dashboards, alerts, and manual triage to automated supply chain execution.
Our AI platform supports large, complex retail and manufacturing networks by deploying specialized AI agents that operate continuously across stores, distribution centers, warehouses, and in-transit operations. These agents detect execution issues, identify root causes, and execute corrective actions - either autonomously or by routing work to the right teams.
Retailers and manufacturers rely on Beamup to replace reactive workflows with consistent, scalable execution — reducing losses, improving performance, and operating with greater confidence at global scale.
Our Mission
To redefine supply chain intelligence by building AI agents that predict, prevent, and resolve inventory health and operational issues in real time.
Job Summary:
We’re looking for an Applied Data Scientist to join one of our product squads. You’ll design, build, and deploy data-driven solutions that combine machine learning, statistical methods, and SQL/rules-based decision logic to power Beamup’s autonomous supply chain intelligence platform. You’ll work closely with data science, engineering, product, and supply chain experts and own solutions end-to-end—from problem definition to production monitoring and iteration.
Responsibilities:
- Deliver data science solutions end-to-end within a product squad: problem framing → data prep/labeling → modeling → deployment support → monitoring → iteration
- Build, train, and improve ML models for supply chain use cases (e.g., inventory risk prediction, demand anomalies, root-cause analysis)
- Define success metrics and evaluation plans with support from senior DS/PM; run error analysis and document learnings
- Work with stakeholders to create and maintain ground truth (label definitions, labeling workflows, QA checks, feedback loops)
- Implement hybrid decision logic by combining ML outputs with statistical methods and SQL/rules-based logic for robustness and explainability
- Analyze large, multi-source operational datasets to identify trends, anomalies, and drivers of performance
- Collaborate with software engineers to productionize solutions (batch and/or real-time), including testing, logging, and basic monitoring
- Monitor deployed models/rules, investigate performance issues (data quality, drift, edge cases), and iterate based on outcomes
- Contribute to team practices: reproducible notebooks/code, documentation, and experiment tracking
Requirements:
- MSc in Computer Science, Data Science, Mathematics, Statistics, Engineering, (or equivalent practical experience)
- 3+ years of experience in applied data science / ML in a product environment (or equivalent practical experience)
- Strong Python skills and experience with common DS libraries (pandas, NumPy, scikit-learn); familiarity with PyTorch/TensorFlow is a plus
- Solid SQL skills (joins, aggregations, window functions) and comfort working with production data in a warehouse/lake
- Experience building predictive or anomaly detection models and performing rigorous evaluation (baselines, cross-validation where relevant, error analysis)
- Ability to translate business questions into measurable metrics and a clear analytical plan (with guidance when needed)
- Experience working with messy real-world data: data validation, debugging pipelines, and collaborating on labeling/ground truth
- Familiarity with taking models to production: packaging/hand-off to engineers, versioning, and understanding monitoring/drift concepts
- Strong communication and collaboration skills with engineering, product, and domain experts; comfortable receiving feedback and iterating fast
Nice to Have (Advantages)
- Experience designing or deploying agentic workflows, AI agents, or multi-step decision systems
- Cloud + Docker + production engineering practices (CI/CD, testing, monitoring)
- Experience publishing academic or applied research (peer-reviewed papers, conference publications, technical whitepapers, or open research work)
Beamup is proud to be an equal opportunity employer and provides equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity or genetics.
You can read more about us at:
And we were also chosen to be one of the 50 most promising Israeli startups of 2023:
https://www.calcalistech.com/ctechnews/article/hjtwkugx2
Beamup is proud to be an equal opportunity employer and provides equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity, or genetics.
You can read more about us at:
And we were also chosen to be one of the 50 most promising Israeli startups of 2023:
https://www.calcalistech.com/ctechnews/article/hjtwkugx2
