דרושים » תוכנה » Data Scientist 23560

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:
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 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:
4+ years of hands-on experience researching, developing, and delivering machine learning models in high-scale, production environments (Python preferred).
Strong background in analyzing large, complex datasets using SQL, Spark, or similar tools.
Deep experience with analytics, machine learning, and deep learning frameworks: Scikit-learn, SciPy, TensorFlow, Pandas, NumPy, PyTorch, Keras.
Demonstrated ability to solve multidisciplinary, data-driven problems.
Excellent teamwork and communication skills.
Experience in application or data security (strong advantage).
Experience with cloud platforms (AWS, Azure, GCP) is a plus.
Experience with Kubernetes (K8s) and microservices infrastructure is a plus.
Experience with CI/CD practices and the full lifecycle of ML model development, from data preparation to deployment and monitoring, is a strong advantage.
Ph.D. or M.Sc. in Computer Science, Engineering, Math, or another quantitative/technical field is valued, but not required if you have strong relevant professional experience.
Strong English and presentation skills are an advantage.

Requirements:
At least 3 years of proven experience in data science or machine learning, with a proven track record of delivering production-grade ML solutions.
Proficiency in Python and commonly used libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch.
Strong knowledge of SQL and experience with querying large datasets.
Familiarity with data pipelines, ETL processes, and data QA.
Strong analytical skills with the ability to translate complex data challenges into actionable solutions.
Deep understanding of ML algorithms and techniques.
Experience in feature engineering, model evaluation, and hyperparameter tuning.
Team player, problem-solver, responsible, delivery-oriented.
Bachelor's degree in Computer Science, Statistics, Applied Mathematics, or a related field.

Requirements:
Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related field.
Minimum of  5 years of experience as a Data Scientist or in a related field, with experience working in a production environment or PHD with relevant experience.
Strong programming skills in Python and proficiency in SQL.
Deep understanding of statistical analysis, machine learning, deep learning and data visualization techniques.
Strong communication and collaboration skills to work effectively in a team environment.
Skills in developing AI agents, such as LLM-based assistants or autonomous workflows - advantage.

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:
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.

Requirements:
MSc (or higher) in Statistics, Machine Learning, Applied Mathematics, or a related quantitative field.
4+ years of experience as a data scientist, with significant focus on insurance pricing or underwriting analytics.
Strong domain expertise in insurance pricing workflows, including rate plan development, evaluation, and optimization.
High proficiency in statistics, machine learning algorithms, data manipulation and analysis.
Extensive experience in research-oriented roles, analyzing business problems from a data science perspective, conducting literature research, and implementing and testing solutions.
Expertise in supervised and unsupervised machine learning models (e.g., GLM, GAM, XGBoost, Deep Learning).
A proactive approach to staying updated with the latest developments in AI and incorporating them to enhance existing products.
A product-driven mindset with a knack for transforming research outcomes into impactful products.
Excellent communication skills, with the ability to articulate experiment goals and methodologies clearly and communicate insights effectively to the team.