דרושים » ניהול ביניים » Senior data Scientist

Requirements:
6+ years of experience in data-driven processes and Fraud/Risk domains

2+ years of managing or mentoring a team of data fraud analysts

Excellent English communication skills, with the ability to explain complex topics clearly and confidently

Strong people skills and a genuine interest in working in customer-facing, collaborative environments

Strong SQL skills and a data-driven approach to problem solving

Good understanding of Machine Learning concepts in fraud detection

Technical depth to work effectively with an internal code-based risk engine

Python and BI tools experience are a plus

Requirements:
BSc or higher in Computer Science, Mathematics, Statistics, or related fields.
4+ years of hands-on experience as a Data Scientist, ideally within mobile, gaming, or social network industries.
Proven experience with AI/ML frameworks and toolkits (Scikit-learn, TensorFlow, PyTorch, LangChain, etc.)
Familiarity with MLOps best practices, model versioning, experiment tracking, and continuous deployment.
Strong knowledge of machine learning techniques: Classification, regression, segmentation, reranking, model interpretability
Solid background in data analysis and statistics; ability to design experiments and interpret results.
Experience working in cloud environments, especially Google Cloud Platform (GCP) - BigQuery, GCS, Vertex AI (a plus).
Comfortable working in fast-paced, production-critical environments with a sense of ownership and accountability.
Advantages:
Experience developing recommendation engines, especially with deep learning and reranking techniques.
Experience with LLM-based applications, prompt engineering, Agents development, etc.

Requirements:
At least 5 years of experience as data scientist /researcher, combining excellent hands-on SQL and Python skills
At least 5 years of experience applying ML algorithms to solve real world business problems (e.g., Logistic Regression, Gradient Boosting Machines, Neural Networks, and unsupervised clustering)
B.Sc in Computer Science, Statistics, Operations Research or equivalent
Solid background with data lake and data warehouse technologies
Great communication skills, Hands-On, independent and out of the box thinker
You might also have
Experience in the Mobile gaming and advertising industries
Proven experience with Airflow development
Experience with big data technologies such as Spark, Trino, SingleStore DB
Experience with Cloud Computing.

Requirements:
5+ years in ML roles with demonstrated production impact
Advanced degree (MS/PhD) in a quantitative field, or equivalent industry depth
Deep expertise in mathematical optimization - convex, constrained, and gradient-based methods
Hands-on experience with Bayesian or hyperparameter optimization
Strong causal inference skills - propensity scoring, uplift modeling, or experimental design
Applied ML experience in optimization domains: pricing, bidding, or resource allocation
Advanced time series modeling for dynamic, decision-making systems
Proven experience deploying and monitoring real-time ML models in production
Familiarity with experiment tracking, model versioning, and performance monitoring

Requirements:
5+ years of experience in deep learning and computer vision research, with a focus on 2D-to-3D modeling, animation or related areas
Experience in 3D reconstruction techniques, including structure from motion, photogrammetry, neural implicit representations, and animation pipelines
Self-driven attitude, end-to-end ownership
MSc in STEM from a leading university
Proven track record of research deliverables
Advantages
Experience with 3D libraries like Open3D, Blender Python API, or MeshLab
Experience with 3D modeling and animation software like Blender, Maya, or Cinema 4D
Hands-on experience with animation techniques and rigging

Requirements:
Required Qualifications
6+ years of hands-on experience delivering production-grade data science and machine learning projects.
Proven track record in applied data science for cybersecurity.
Deep expertise in probability, statistics, and machine learning, with a proven ability to select, adapt, and apply advanced algorithms to real-world problems.
Proven deep learning experience, including model design, training, and evaluation.
Strong proficiency in Python with solid working knowledge of SQL.
Advanced degree (MSc or PhD) in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Mathematics, or a closely related field.
Demonstrated ownership of end-to-end research POCs, from problem formulation and experimental design through execution, analysis, and final recommendations.
Strong emphasis on engineering-quality, production-ready code with high standards for reliability, scalability, and maintainability.
Excellent communication skills, with the ability to clearly articulate complex technical insights to both technical and business stakeholders.
Preferred Qualifications
Direct experience with detection and response platforms (XDR, EDR, or NDR).
Experience working with Big Data platforms (e.g., GCP, BigQuery, Dataflow).
Familiarity with cloud-native architectures and MLOps tools for managing the model lifecycle at scale.