דרושים » דאטה » Senior Data Scientist

Requirements:
MSc in Computer Science/Engineering or related field with a focus on applied statistics, AI, machine learning, or related fields - a must.
6+ years of production environment experience, working with predictive and probabilistic models, clustering algorithms, classification models, search and recommendation techniques - a must.
Proven record for successful production implementation of translating product/business requirements into a technical solution.
Team player, Ability to handle several tasks simultaneously.
Strong knowledge in Python, SQL, and NoSQL.
Spark and Big data technologies experience an advantage.
Research experience - an advantage.
Experience with e-commerce - an advantage.

Requirements:
Proven strong expertise (8+ years) as a data scientist and machine-learning researcher.
Proven strong expertise (8+ years) in Python, with a production-level design and coding skills and hands-on experience with coding machine learning / statistical modeling based solutions
M.Sc. in Computer Science, Mathematics, Engineering or a related field, with strong theoretical background in supervised & unsupervised modeling and various other statistical modeling techniques
High-level experience with databases approaches, such as SQL and document-oriented (e.g. MongoDB) and big data
Experience in data analysis and visualization
Strong problem solving and critical thinking skills
Can-do approach
Background in Cybersecurity - an advantage
Theoretical and practical background in Generative AI - an advantage

Requirements:
M.Sc. in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field.
5+ years of experience in applied AI research.
Strong programming skills, particularly in Python and ML frameworks (e.g., TensorFlow, PyTorch).
Solid understanding of NLP.
Experience with modern Large Language Models (LLM) and generative models.
Proven expertise in designing, implementing, and evaluating deep learning models in a production environment.

Requirements:
5 + years of hands-on experience developing and deploying machine-learning or data-science solutions with Python and SQL.
Proven, end-to-end experience building AI- and machine learning-based solutions from prototype to production deployment.
Demonstrated success shipping data-intensive services to production on cloud infrastructure (AWS preferred) using data tools such as PostgreSQL, Databricks, Spark, or Airflow.
Deep understanding of machine-learning fundamentals and practical expertise with frameworks such as TensorFlow, PyTorch, or scikit-learn.
Expertise in machine learning metrics and quality control.
Solid understanding of software-engineering best practices (including design patterns, data structures, and version control).
Excellent interpersonal and communication skills, with the ability to explain complex technical concepts to non-technical stakeholders and collaborate across teams.
Its even better if you have:
Experience with Agile development in fast-paced, delivery-driven environments.
Familiarity with CI/CD practices, containers, Kubernetes, and serverless or microservice architectures.
Experience with geospatial analysis, government data, survey research, or civic-tech applications.
A track record of contributing to open-source projects.
A college or graduate degree in a relevant field.

Requirements:
Natural scientific curiosity and ability to handle complex problems
At least 6 years of experience in hands-on data science projects
High proficiency in python and at least good familiarity with SQL
Advanced degree (MSc or PhD) in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Mathematics, or a related field or equivalent military experience required
Deep understanding of probability, statistics, and machine learning models with a proven track record of selecting, modifying, and applying advanced algorithms to solve practical problems
Demonstrated ability to run end-to-end research POCs, from conceptualization to solutions, including designing, executing, analyzing, and concluding research methodologies and outcomes
Good communication skills, with the ability to convey complex research findings clearly and effectively to both technical and business audiences
Preferred
Background in the cybersecurity domain
Experience with recommender systems
Experience working with big data platforms (e.g., GCP)
Experience with LLM-based algorithm design
Familiarity with cloud-native architectures and services for data processing.

Requirements:
What skills & knowledge should you bring?
Degree in Computer Science or Mathematics, or equivalent experience.
Experience with collecting, building, and tailoring large datasets for training machine learning models.
Ability to work collaboratively to translate business requirements into technical solutions.
Willingness and ability to work in a diverse, globally distributed team
a proven track record of working on ML products in production.
Past experience in the cyber domain.
Experience designing, training, and evaluating models used in production systems.
The ability to work on difficult problems alone. Our ML problems might be "classical", but the actual setting of our problems is far from easy or convenient.
Strong communication skills. Our team relies on strong communication between us, since we have a diverse and sometimes exclusive set of skills, yet our end product relies on all team members. Thus, we need our team members to be able to communicate with people outside our team (with a wide range of backgrounds / positions, product / support / engineering, )
A fiery determination and a strong team-player mindset the team's defining trait is an 'all hands on deck' attitude.

Experience / interest in some of these areas are an advantage:
Security products, especially detection systems.
Cloud infrastructure / MLOps.
Experience with Spark / Pyspark / Databricks.

Requirements:
What Experience Will Drive to Success:
* Bachelors degree in data Science, Computer Science, Computer Engineering, or related field.
* 2+ years of experience in AI/ML engineering, with a proven track record of building and deploying ML & AI systems.
* Strong programming skills in Python and experience with ML frameworks such as TensorFlow, PyTorch, and Scikit-Learn.
* Hands-on experience with Big Data processing frameworks (Apache Spark, Dask, Ray).
* Hands-on experience with LLMs and AI Frameworks (LangChain, OpenAI, HuggingFace, LangGraph, etc.)
* Experience with Git and Jenkins.
* Strong problem-solving skills, a passion for innovation, and a self-driven mindset.
* Excellent communication and collaboration skills.
* Familiarity with AWS AI/ML services and cloud-based deployments (Advantage).
* Experience working with MLOps tools, including model registry, experiment tracking, and model serving (Advantage).
What We Are Looking For Independent and Self-Driven: Were building an AI Department from the ground up, so we need someone who is proactive, takes ownership, and thrives in a startup-like environment. Passion for Innovation: Whether its building scalable data infrastructure or creating advanced AI models, we are looking for someone passionate about solving complex challenges and delivering innovative solutions. Collaboration Skills: Appdome is all about teamwork. You will collaborate with engineers, data scientists, and product teams to build impactful solutions. Strong communication and interpersonal skills are key. Adaptability and Problem-Solving: Things move quickly at Appdome. You should be able to adapt to changing requirements and quickly solve problems in a fast-paced, dynamic environment. Can-Do Attitude: Were looking for motivated individuals who take the initiative, face challenges head-on, and can work independently while contributing to team success. About the Company: Appdome'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 Appdome, 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.

Requirements:
MSc in Computer Science/Engineering or related field with a focus on applied statistics, AI, machine learning, or related fields - a must.
6+ years of production environment experience, working with predictive and probabilistic models, clustering algorithms, classification models, search and recommendation techniques - a must.
Proven record for successful production implementation of translating product/business requirements into a technical solution.
Team player, Ability to handle several tasks simultaneously.
Strong knowledge in Python, SQL, and NoSQL.
Spark and Big data technologies experience an advantage.
Research experience - an advantage.
Experience with e-commerce - an advantage.

Requirements:
Advanced degree (M.Sc. or Ph.D.) in Electrical Engineering, Physics, Applied Mathematics, Computer Science, or a related quantitative discipline.
5+ years of hands-on experience in developing and deploying machine learning, signal processing, or algorithmic solutions, with emphasis on raw or low-level data (e.g., sensor data, audio, video streams, or medical imaging).
Proven expertise in time-series analysis and handling large-scale, complex datasets from acquisition to production deployment.
Strong Python programming skills, with the ability to write clean, modular, and testable production-grade code.
Demonstrated experience deploying ML/DSP pipelines into production environments, ideally in high-availability systems.
Familiarity with ML/DL frameworks such as PyTorch, TensorFlow, scikit-learn, and gradient-boosting libraries (e.g., XGBoost, LightGBM).
Strong collaboration and communication skills, with the ability to work effectively across interdisciplinary teams including software engineers, physicists, and external stakeholders.

Requirements:
5+ years experience as a Data Scientist
2+ years experience working with Deep Learning.
Experience working with recommender systems - an advantage
Hands-on experience building and deploying deep learning models to production
High level scripting and programming skills in Python
Superior verbal, visual, and written communication skills to educate and work with cross functional teams on controlled experiments.
Team player, responsible, delivery-oriented
Troubleshooter, problem-solver who knows how to navigate trade-offs
Work experience as a data analyst - an advantage
At least a Master's degree in Computer Science, Math, Physics, Engineering, Statistics or other technical field.
Experience in ML over user personalization, ad-tech, or highly imbalanced data- an advantage.