לוח משרות דרושים Data Scientist משרה מלאה

Requirements:
4+ years of hands-on experience in fraud analytics, data science, or risk modeling - Must.
Proven experience in the Fintech/Fraud Prevention Domain - Must.
Proven ability to take projects from A to Z in building data infrastructure, anomaly detection, and graph-based fraud detection solutions - Must.
Strong practical proficiency in Python, SQL, MLOps and fraud-related data tools - Must.
Strong background in e-commerce or payments - Advantage.
A self-starter mentality - someone who identifies opportunities, takes initiative, and drives improvements with minimal direction.

Requirements:
Master degree or higher in Computer Science/Mathematics/Physics,/Electric engineering or equivalent is a must.
Strong theoretical background in Machine Learning.
An understanding of linguistics theory and principles (semantic relations, parsing methods, etc.).
2+ years experience with Python.
3+ years experience with conducting NLP research (Specifically: Text) using Deep Learning models (RNN, Transformers, etc) and frameworks (PyTorch, Tensorflow, etc.).
Educate our customers on new and existing features, best practices, and a variety of use cases across industries. This is achieved by planning and hosting online demos, consultations, and screen shares on both a one-to-one and one-to-many basis.

An in-depth understanding in one or more of the following will be a plus:
Optimization.
Information theory.
Probability and statistics.
Bayesian methods.
Publications at top-tier conferences (i.e, ACL, EMNLP, ICML, NeurIPS).
Experience with distributed DL.
Experience with cloud ML (GCP, AWS, etc.).

Requirements:
Requirements:
5+ years of experience in machine learning, working with tabular and text data.
Track record of translating research projects into business impact.
MSc or PhD in a related fieldStats/CS/Math/EE is an advantage.
Experience with NLP, open-source LLMS, recommendation systems, and scalable classic ML (classifications and clustering), as well as similarity metrics.
Excellent interpersonal skills and a strong collaborator.
Solid applied statistics skills, such as descriptive statistics, distributions analysis, and statistical testing.

Proficient in Python:
GenAI Magic: TensorFlow, PyTorch, Hugging Face Transformers, Sentence Transformers, OpenAI API.
Next-Gen Tools: LangChain, LlamaIndex.
Data Science Essentials: Pandas, Sklearn, NumPy, SciPy, Matplotlib.
NLP Essentials: NLTK, SpaCy.
MLOps & Automation: MLflow, Kubeflow.

Requirements:
5+ years of experience in data science, with experience in managing full-cycle projects from initial concept to production deployment.
PhD in Computer Science, Data Science, Statistics, Mathematics or a related field .
Comprehensive understanding of machine learning and deep learning principles and techniques, including hands-on experience.
Specialized expertise in NLP (Transformers, LLMs) and computer vision (multimodality is an advantage).
Ability to write production-ready code.
Publications and talks at leading conferences - an advantage.

Requirements:
* MSc in Computer Science, Engineering, or a related field
* Focus on AI, ML, or DS.
* 5+ years of experience in DS roles, with a strong emphasis on building and deploying machine learning models in production environments.
* Expertise in Python and SQL.
* Experience with machine learning frameworks such as TensorFlow or PyTorch.
* Familiarity with cloud platforms (e.g., AWS, GCP) and containerization tools (e.g., Docker, Kubernetes).
* Proven experience in developing, fine-tuning, and deploying ML models, particularly in NLP.
* Ability to translate complex business problems into data-driven solutions.
* Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders. Preferred Qualifications:
* Background in academic or industrial research in AI.
* Familiarity with the e-commerce domain and related data challenges.
* Previous experience leading projects in a DS capacity.

Requirements:
6+ years of hands-on experience as a data scientist, including at least 2 in early-stage startups or fast-paced environments.
3+ years leading full-cycle ML projects from research to production, adoption, and monitoring.
Deep familiarity with building ML products using textual inputs.
Experience building LLM-based systems.
Leverage AI-powered tools like Cursor, Claude Code, GitHub Copilot, or ChatGPT as part of your workflow to accelerate development, debug faster, and explore ideas more effectively.
You bring strong product and user intuition youre not just building models, youre solving real problems.
Youre a great teammate: collaborative, communicative, and fun to work with.
Masters degree in Computer Science, Engineering, Statistics, or a related technical field.

Requirements:
Minimum 3 years of professional experience in Data Science roles
Hands-on experience in networking and/or cybersecurity domains
Strong foundation in classical machine learning methods (supervised, unsupervised learning, clustering)
Practical experience with deep learning frameworks such as TensorFlow or PyTorch, including NLP techniques
Proven experience deploying models on cloud platforms like AWS, Azure, or Google Cloud
Excellent analytical, problem-solving, and communication skills
Self-motivated, collaborative, and able to work independently
How to Stand Out
Experience building agentic systems using Retrieval-Augmented Generation (RAG), including tool orchestration, benchmarking frameworks, and vector databases (e.g., FAISS, Pinecone)
Prior experience working in a fast-paced, high-growth environment
Advanced degree (MSc or PhD) in Computer Science, Statistics, Mathematics, or a related quantitative field.

Requirements:
Bachelor's degree in Finance, Accounting, Business Administration, Data Science, or a related field.
Minimum of 2+ years of experience as a Business Analyst or similar role within the SaaS industry.
Strong analytical skills with experience in analyzing large datasets.
Strong understanding of accounting principles and financial reporting standards and their application to SaaS businesses.
Understanding of key SaaS metrics (CAC, retention, renewal rate, churn rate, ACV, MRR, ARR, etc.) and their impact on the financial health of the business.
Proficient in using SQL, Python, or other relevant data analysis tools.
Expert in using BI tools like Tableau, Power BI, or similar platforms to create impactful data visualizations.
Excellent communication, presentation, and interpersonal skills.
Ability to work independently and as part of a team.
Strong attention to detail and problem-solving skills.

Requirements:
Holds a B.Sc. in Computer Science/Mathematics/Physics or any other relevant field - Required
Has 3+ years of experience with statistical and machine learning tools - Python, R, etc.
Strong communicative and verbal abilities to lead and guide customers through the logic of custom-built models
Has previous experience developing machine learning/ image processing/NLP or similar algorithms
Demonstrated experience utilizing probability theory and statistics
Familiarity with SQL
Experience with Big Data tools and cloud infrastructure; PySpark, AWS (big advantage)
Strong analytical skills; experience analyzing and processing tabular data, and extracting insights (big advantage).

Requirements:
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Statistics, or a related quantitative field.
7+ years of progressive experience in data-focused roles, with at least 2+ years in a leadership position managing multiple data functions (e.g., data engineering, BI, data science).
Proven experience leading and scaling teams in a fast-paced, high-growth technology company, preferably within the ad tech, media, or e-commerce industries.
Deep understanding of data warehousing principles, ETL/ELT processes, and large-scale data architecture (e.g., Snowflake, BigQuery, Redshift, Databricks).
Strong technical background in data engineering concepts, including distributed systems, streaming data, and big data technologies (e.g., Spark, Kafka).
Solid experience with BI tools and platforms (e.g., Tableau, Looker, Power BI) and their implementation.
Familiarity with data science methodologies, machine learning concepts, and their practical applications.
Excellent communication, interpersonal, and presentation skills, with the ability to articulate complex technical concepts to non-technical stakeholders and influence decision-making at all levels.
Strategic thinker with a hands-on approach and a proven track record of delivering results.

Requirements:
- Bachelors degree in data Science, Computer Science, Computer Engineering, or related field. - 2+ years of experience in data Science roles. - Proven experience managing AI/ML project lifecycles from conception to deployment. - Deep understanding of classic ML, deep learning, and LLMs. - Strong proficiency in Python and experience with frameworks such as PyTorch, Scikit-Learn, and TensorFlow. - Hands-on experience with low-level programming in C / C ++. - Team player with strong collaboration and communication skills. - Quick learner with ability to adapt to new tools, methods, and frameworks. Preferred Qualifications: - Background in mobile app research or development ( Android / IOSgreenTxtBg!). - Image processing experience. - Reverse engineering experience with tools like IDA, gdb, and lldb. - Knowledge of OS internals. - Cybersecurity background with understanding of threat landscapes and attack vectors. About the Company:our company's mission is to protect every mobile app worldwide and its users. We provide mobile brands with the only patented, centralized, data -driven Mobile Cyber Defense Automation platform. Our platform delivers rapid no-code, no-SDK mobile app security, anti-fraud, anti-malware, anti-cheat, anti-bot implementations, configuration as code ease, Threat-Events threat-aware UI / UX control, ThreatScope Mobile XDR, and Certified Secure DevSecOps Certification in one integrated system. With our company, mobile Developers, cyber and fraud teams can accelerate delivery, guarantee compliance, and leverage automation to build, TEST, release, and monitor the full range of cyber, anti-fraud, and other defenses needed in mobile apps from within mobile DevOps and CI/CD pipelines. Leading financial, healthcare, m-commerce, consumer, and B2B brands use our company to upgrade mobile DevSecOps and protect Android & IOS apps, mobile customers, and businesses globally. Today, our company's customers use our platform to secure over 50,000+ mobile apps, with protection for over 1 billion mobile end users projected.
we are an Equal Opportunity Employer. We are committed to diversity, equity, and inclusion in our workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law. All qualified applicants will receive consideration for employment without regard to any of these characteristics.