דרושים » תוכנה » Data Scientist 23019

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:
5+ years of experience in leading and managing data science and machine learning projects, preferably in the intersection of AI and cybersecurity
Experience with distributed cloud systems - Hands-on familiarity with cloud systems that are distributed
Strong knowledge of deep learning models and common model architecture such as transformer models, CNNs, RNNs
Knowledge of programming languages that are used in AI research, such as Python, and experience with AI frameworks (e.g., Hugging Face, LangChain, OpenAI, scikit-learn, TensorFlow, PyTorch)
Ability to work independently in a fast-paced, and come up with creative solutions to challenging problems
Excellent communication (both written and verbal) and presentation skills
ADVANTAGE:
An M.S. or Ph.D. degree in computer science, statistics, or related field OR equivalent work experience
Knowledge of cybersecurity principles, attack vectors, and defense mechanisms.

Requirements:
MSc in Computer Science, Engineering, or a related field with a 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:
At least 3 years of experience in product-oriented data analytics/feature engineering/data science/research /hypothesis lead research.
Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, etc.
Experience with productizing machine learning models and/or implementation of Data Pipelines.
Experience working with large and complex data sets.
Experience with Cloud services.
BSc in Computer Science/Software Engineering or equivalent knowledge.
Fast learning and ability to dive into new technologies and new pieces of code.
Enthusiastic and motivated to improve.
Independent thinker with a desire to learn.
Advantages
Experience with Kusto and DataBricks
Relevant masters degree
Proven experience in Cyber Security.
Experience in common Networking protocols.
Big Data (Hadoop, NoSQL, Elastic Search, Spark).

Requirements:
Reach out if you have:
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./PhD in a relevant field with strong quantitative skills.
5+ years of hands-on experience as a Data Scientist in an innovative and fast-paced environment.
Strong analytical mindset with a deep understanding of data limitations, sampling, frequency, manipulation, and cleaning techniques.
3+ years of practical experience with the Python data science toolbox
Experience working with large datasets and familiarity with the Big Data ecosystem
Proven track record of delivering data-driven solutions achieving measurable outputs.
Excellent communication and interpersonal skills, with the ability to collaborate effectively within a team.
Self-starter with a "get-things-done" attitude and a proactive approach to problem-solving.
Continuous learner who is passionate about staying up-to-date with the latest data science trends and technologies.
Additional Nice to Have:
Strong data visualization and presentation skills.
Experience working in cloud-based environments.
Maritime background and passion

Requirements:
At least 4+ years of relevant experience and track record in Data Science: Machine Learning, Deep Learning and Statistical Data Analysis.
MSc or PhD degree in CS or Mathematics, Bioinformatics, Statistics, Engineering, Physics or similar discipline.
Strong hands-on experience in Python with the focus being on statistical algorithms development.
Experience with data science libraries such as: sklearn, pandas, numpy, pytorch/tensorflow
Team player, able to work in collaboration with subject matter experts, with ability to clearly present and communicate findings.
Proven ability to build and deliver data solutions in a short time frame.
Experience with AWS, docker, and development methodologies - an advantage
Experience with Snowflake and Databricks an advantage.
Active Github, Kaggle member an advantage.
Cyber security background an advantage.

Requirements:
Masters in Computer Science/Statistics/Economics/Engineering or related field with a focus on applied statistics, AI, machine learning, or related fields
5+ years applying machine learning to real-world problems in an industrial setting.
Strong engineering and coding skills, with ability to write high performance production code. Ability to lead, envision and implement improvements of our ML solution and pipelines
Proficiency in Python, SQL, Spark.
Hands-on experience in Machine learning frameworks such as Scikit-learn, TensorFlow, Pandas, Numpy etc.
Strong understanding of evaluation methods for recommender systems and ability to run offline and online using experimental design
Preferred proficiency with data pipelines in Hadoop/Spark in a cloud environment
Ability to write and execute complex queries in SQL against different database architectures
Working knowledge of agile development processes and methodologies
Strong analytical & problem-solving skills, and excellent communication skills

Requirements:
At least 3-4 years of relevant experience and track record in Data Science: Machine Learning, Deep Learning, and Statistical Data Analysis.
Proven experience in developing and deploying production-level models within enterprise environments.
MSc or PhD degree in CS or Mathematics, Bioinformatics, Statistics, Engineering, Physics, or similar discipline.
Strong hands-on experience in Python with a focus on statistical algorithms development.
Experience with data science libraries such as: sklearn, pandas, numpy, pytorch/tensorflow.
Team player, able to work in collaboration with subject matter experts, with the ability to clearly present and communicate findings.
Proven ability to build and deliver data solutions in a short time frame.
Experience with AWS, Docker, and development methodologies - an advantage.
Active Github, Kaggle member an advantage.
Background in data loss prevention or related fields an advantage.

Requirements:
Extensive Data Science Experience: You have at least 7 years of experience in data science, with a proven track record of executing end-to-end AI projects and successfully deploying models to production.
Strong Programming & Technical Expertise: You are highly proficient in Python (or another relevant programming language) and have hands-on experience with deep learning frameworks like TensorFlow and PyTorch.
NLP & Deep Learning Expertise: You have solid background in natural language processing and deep learning applications, including text classification, sequence modeling, entity recognition, and embedding-based methods.
Research-Oriented Problem Solver: You are skilled in leading research initiatives, exploring new methodologies, and implementing innovative AI solutions to solve real-world challenges.
Collaborative & Business-Minded: You have experience working cross-functionally with management, business stakeholders, and technical teams to align AI solutions with business objectives.
Strong Communicator & Strategic Thinker: You can clearly articulate complex AI concepts to both technical and non-technical stakeholders, contributing to company-wide decision-making.