לוח משרות דרושים Data Scientist

Requirements:
Requirements:
M.Sc / PhD in Computer Science/Mathematics/Statistics/Engineering or related fields.
4+ years of experience of work as a data scientist.
Working on big data projects and environments.
5+ years of experience with python and data science related frameworks and packages (Jupyter, Pandas, Numpy, Scipy, ScikitLearn, Plotly).
Experience with Deep Learning (Pytorch / Tensorflow) within the following disciplines: NLP / Vision / Tabular Data / Time Series Forecasting.
Strong statistical, analytical & problem solving skills.
Hands on SQL skills, ability to understand, write and maintain complex queries.
Team player with strong communication skills.
Strong knowledge of software-engineering principles such as modularity, automated testing, and documentation.
Fluent in english.

Advantages:
Working in research teams.
Experience of reading and reproducing academic papers.
Experience of conducting experiments and optimizing models.
Experience with Google Cloud Platform (BigQuery, CloudRun, CloudFunctions, VertexAI)
Experience with Linux environment and shell scripting.
Domain experience of game analytics (LTV, UA, Creative Analysis, Time Series Analysis).
Experience with leading end-to-end projects.

Required Skills:
Coding.
Communication skills.
self learner.
Methodological.
Deep Learning.

Requirements:
3+ years working as a Backend engineer
3+ years working as NLP/ML/DS applied researcher (or equivalent experience)
B.S. in Computer Science, Electrical Engineering, or Mathematics
Enthusiasm for the latest GenAI technologies
Familiarity with modern backend frameworks, tools, and architecture
Experience with production-grade projects
Eagerness to learn quickly and adapt to new technologies and frameworks
Experience in building LLM applications (preferred)
Ability to work in an office environment a minimum of 3 days a week.

Requirements:
* Bachelor's degree in Statistics, Mathematics, data Science, Economics, or a highly quantitative field - Must (Advanced degree an advantage)
* 3+ years of experience in data analysis, statistical modeling, and predictive analytics within the financial services industry, preferably in Fair Lending or credit decisioning
* Strong technical proficiency in data science tools and programming languages such as Python, R, SQL, with experience in developing predictive models and Machine Learning algorithms.
* Strong knowledge of advanced analytics and Machine Learning techniques such as Regression and Classification algorithms including linear and logistic regression, random forest and gradient boosting, k-nearest neighbors, support vector machines (SVMs) and other techniques
* Experience working with cloud-based data platforms and technologies such as AWS and Sagemaker for scalable data analytics and Machine Learning
* Experience working with large-scale datasets
* Ability to communicate findings and recommendations to stakeholders
* Strong problem-solving skills while paying attention to detail
* Ability to work independently and collaboratively in a fast-paced environment, managing multiple projects and priorities simultaneously A Bonus
* Experience with Fair Lending analytics preferred
* Familiarity with Fair Lending regulations such as the Equal Credit Opportunity Act (ECOA), Fair Housing Act (FHA), and Home Mortgage Disclosure Act (HMDA) or other consumer financial protection laws and regulations preferred
* Experience in the financial service sector including lending products or credit risk management preferred
* Experience with data visualization tools such as Tableau and Power BI an advantage
* Experience with Machine Learning techniques, such as decision trees, random forests, or gradient boosting an advantage.

Requirements:
Minimum of 5 years of experience as a Data Scientist.
Deep understanding of data science principles, machine learning, and statistics concepts.
Experience with Bayesian Nonparametrics and mixed integer programming.
Proficiency in various programming and database languages, such as Python, PySpark, SQL, and optimization modeling language such as Pyomo.
Experience addressing real-world analytical problems using machine learning, statistical modeling, or similar quantitative approaches.
Experience in cloud-based ecosystems such GCP, AWS, or Azure for development and deployment of models.
Experience working on global teams collaborating via tools such as Jira, Teams, ADO.
Advanced level of English.
Working Israeli permit- a must.

Requirements:
* Bachelor's degree or equivalent experience in quantitative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
* At least 4 years of experience in a data Science role
* Full ( data Science) Stack experience: data pipelining, model building, experimentation, and analysis/reporting
* Strong working knowledge of SQL: ability to dive into raw data and debug problems
* Deep understanding of Machine Learning algorithms and experience with production pipelines. Advantage: experience with Causal Inference, multi-armed bandits
* Experience setting up data /ML pipelines in production environments (e.g. working with MLOps, DBT, etc.)
* Experience with designing A/B tests in complex environments
* Fluency in Python

Requirements:
MSc or Ph.D. in Computer Science or a related field.
A minimum of five years of experience as a data scientist.
Experience in deep neural networks, especially in transformer architecture and graph embeddings.
Full proficiency with open-source ML frameworks such as TensorFlow or PyTorch.
Previous experience in a production environment.
Advanced Python skills with a hands-on attitude towards problem-solving.
Strong interpersonal skills, logical reasoning, and a collaborative mindset.
Advantages:
Familiarity with natural language processing (NLP), large language models (LLMs), and Generative AI ecosystems.
Demonstrated an ability to deliver high-impact projects with measurable results.

Requirements:
Proficient in Hebrew and English both written and verbal, sufficient for achieving consensus and success in a remote and largely asynchronous work environment - Must
Bachelor's degree in Statistics, Mathematics, Data Science, Economics, or a highly quantitative field - Must (Advanced degree an advantage)
3+ years of experience in data analysis, statistical modeling, and predictive analytics within the financial services industry, preferably in Fair Lending or credit decisioning
Strong technical proficiency in data science tools and programming languages such as Python, R, SQL, with experience in developing predictive models and machine learning algorithms.
Strong knowledge of advanced analytics and machine learning techniques such as Regression and Classification algorithms, including linear and logistic regression, random forest and gradient boosting, k-nearest neighbors, support vector machines (SVMs) and other techniques
Experience working with cloud-based data platforms and technologies such as AWS and Sagemaker for scalable data analytics and machine learning
Experience working with large-scale datasets
Ability to communicate findings and recommendations to stakeholders
Strong problem-solving skills while paying attention to detail
Ability to work independently and collaboratively in a fast-paced environment, managing multiple projects and priorities simultaneously
A Bonus:
Experience with Fair Lending analytics preferred
Familiarity with Fair Lending regulations such as the Equal Credit Opportunity Act (ECOA), Fair Housing Act (FHA), and Home Mortgage Disclosure Act (HMDA) or other consumer financial protection laws and regulations preferred
Experience in the financial service sector including lending products or credit risk management preferred
Experience with data visualization tools such as Tableau and Power BI an advantage
Experience with machine learning techniques, such as decision trees, random forests, or gradient boosting an advantage.

Requirements:
. This role implies hands-on use of Python, SQL and advanced data Science techniques to utilize unstructured and structured data. It is important that our candidate has strong, practical Python programming skills, and strong familiarity with OCR/ NLP /LLM/ML processes. Required technical skills: Proficiency in Python Practical LLM development knowledge- experience in training, fine-tuning, and optimizing LLMs At least 3 years of ML/ NLP modeling experience Experience with NLP tasks such as text classification, named entity recognition, sentiment analysis, and machine translation. Knowledge of SQL and NoSQL databases. Knowledge of deploying models to production environments using Docker, Kubernetes, and CI/CD pipelines. Proficiency with Git and other version control systems Experience with cloud platforms like AWS or Google Cloud for model training and deployment. Applied background in development and deployment patterns, understanding of how to write maintainable code and the importance of testing Required soft skills Both a team player and an independent professional striving for excellence
A positive can-do attitude, multi-tasking, highly motivated and result-focused
Flexible thinker and savvy learner. Available for on-site assignments at customer premises Security clearance - at least level 3 - a big advantage
Education: Degree in a Relevant Field: A bachelor's or master's degree in Computer Science, data science, statistics, mathematics, engineering, or a related field.

Requirements:
Bachelor or Masters degree in technical discipline such as Computer Science, Information Systems, Mathematics, Engineering (or another technical field).
3 years as a data Engineer on a data, analytics, or data science team Experience with building streaming pipelines at scale using Spark Advanced experience with AWS cloud services Advanced working SQL experience as well as performance turning Experience with data pipeline workflow management tools such as Airflow Experience working with agile methodologies and working in cross-functional teams

Requirements:
Bachelor's degree in data Science/ Computer Science / Engineering/ Statistics/ Mathematics or a related field.
Proven track record of excellence in solving Machine Learning challenges.
4 years of industry experience as a data Scientist, working with Machine Learning, data science, statistical or probabilistic modeling including writing code in a production environment Strong Python programming & SQL skills.
Solid understanding of data analysis, statistical modeling, and Machine Learning techniques.
Familiarity with data pre-processing techniques and data cleaning methodologies.
Strong problem-solving skills and the ability to think analytically. Acting and thinking as an owner, with production environment in mind Team player with excellent communication skills.