Manager Data Management
Posted 13 days ago · 0 applicants
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The role in plain words
This role involves managing data processes and quality control to support AI solutions. Day to day, you will coordinate annotation operations, collaborate with Product and Deep Learning teams, handle data cleaning and dataset organization, and develop tagging guidelines.
- Academic degree in Computer Science, Engineering, Data Science, or a related field
- At least 1 year of experience in a similar data/ML/data operations role
- High-level English (written and spoken)
- Strong Python skills (data processing, scripting, automation)
- Solid understanding of ML model training workflows (Train/Test Split, validation techniques, overfitting/underfitting, model evaluation metrics, etc.)
- Hands-on experience in data management or data operations
- Experience with SQL, Pandas, NumPy or similar data tools
- Familiarity with data management / annotation platforms such as Databricks, Roboflow, Dataloop, SuperAnnotate
- Experience or interest in image processing / computer vision
- Knowledge of model versioning, QA processes, or LLM-based tools
Extracted from the job description · kept up to date automatically
Who this suits
This role suits detail-oriented candidates with a degree in Computer Science or a related field, strong Python skills, and at least 1 year of experience in data or ML operations. It is less ideal for those looking for a non-technical role or without experience in ML training workflows and data pipelines.
Full job description
Original listing · kept for reference🚀We’re Hiring – Data Manager
📍 Location – Bnei Brak, BSR 2
Join our growing team at SkillReal and play a key role in managing and optimizing data processes that power cutting-edge AI solutions.
We're looking for a detail-oriented, proactive Data Manager who thrives in a fast-paced tech environment.
👍Role Responsibilities:
🔹Manage Data Intake & Quality Control
Oversee incoming data flows, ensuring datasets meet quality standards and align with project requirements. Define and maintain proper train/test splits and ensure data consistency across pipelines.
🔹Lead Annotation Operations
Coordinate day-to-day work with both in-house and outsourced annotation teams. Distribute tasks, manage priorities, monitor progress, and perform quality assurance to ensure high labeling standards.
🔹Cross-Team Alignment (Product & Algorithms)
Collaborate closely with Product and Algorithm (Deep Learning) teams to ensure data requirements are well-defined, feasible, and aligned with model capabilities before annotation begins.
🔹Own Ongoing Data Operations
Handle daily data-related tasks including data cleaning, platform management, dataset organization, and occasional hands-on annotation when needed.
🔹Define Annotation Protocols
Develop clear tagging guidelines and methodologies for new object types. Train annotation teams on protocols and continuously refine processes to improve accuracy and efficiency.
✅ Must-Have Qualifications:
🔹 Academic degree in Computer Science, Engineering, Data Science, or a related field
🔹 **At least 1 year of experience in a similar data/ML/data operations role**
🔹 Strong organizational skills and high attention to detail
🔹 High-level English (written and spoken) – working with global teams
🔹 Strong Python skills (data processing, scripting, automation)
🔹 Solid understanding of ML model training workflows
(Train/Test Split, validation techniques, overfitting/underfitting, model evaluation metrics, etc.)
🔹 Experience working with data pipelines and large datasets
🔹 Independent, fast learner, proactive, and comfortable in a startup environment
⭐ Advantages:
🔹 Hands-on experience in data management or data operations
🔹 Experience with SQL, Pandas, NumPy or similar data tools
🔹 Familiarity with data management / annotation platforms such as:
Databricks, Roboflow, Dataloop, SuperAnnotate
🔹 Experience or interest in image processing / computer vision
🔹 Knowledge of model versioning, QA processes, or LLM-based tools
🔹 Familiarity with Git, Jupyter Notebooks, or similar tools
🔹 Familiarity with CAD formats (e.g., STEP files) and experience working with them across different platforms or tools
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Questions about this role
- This listing did not state a salary. We only show pay when the employer publishes it.
- Academic degree in Computer Science, Engineering, Data Science, or a related field, At least 1 year of experience in a similar data/ML/data operations role, High-level English (written and spoken), Strong Python skills (data processing, scripting, automation), Solid understanding of ML model training workflows (Train/Test Split, validation techniques, overfitting/underfitting, model evaluation metrics, etc.)