דרושים » מדעים מדוייקים » data Scientist בחברת סטארט-אפ העוסקת בתחום הפרסום

We are looking for an outstanding Senior Data Scientist to join the team and revolutionize how investment is done. Youll be harnessing the power of machine learning models and advanced mathematical techniques to develop the first-ever real-time, no-code corporate credit score platform.
If you are a bright, out-of-the-box thinker, and love coming up with solutions for real-life big-data problems, and have expertise in Large Language Models and Time Series Analysis, we are looking for you!
Responsibilities:
Research of state of the art generative AI models as well as classical machine learning models.
Define data collection plan and requirements
Build models from POC to production-ready
Work closely with ML engineering team driving production release and performance monitoring
Provide guidance to the product team and user community to increase product effectiveness

One Security Operations Center (SOC) is a new team under Modern Protection & Security Operation Center, our vision is to empower every SOC team to protect their entire digital estate, optimize for their unique environment and needs. We build the ultimate unified one-stop-shop solution, making SOC teams most effective and efficient and deliver optimized protection that meets customers where they are, leading Extended Detection and Response (XDR)+ Security Information and Event Management (SIEM) market.
We are looking for an innovative data scientist with NLP expertise, strong technical skills and desire to make significant impact through data and research. A successful candidate will be an excellent hands-on applied data scientist who is enthusiastic about NLP, LLMs, data, security, and real-world problem solving
Responsibilities
As a senior data scientist on our team, you will work closely with other data scientists, security experts, software engineers, and product managers to tackle many different types of problems. You will utilize generative AI tools, anomaly detection algorithms, supervised and unsupervised learning methods, statistical methods, time series analysis, and more, to help customers investigate security incidents and protect their environments. You will be up to date with our customers needs and the competitive landscape and work with internal and external teams to build advanced solutions for SIEM and XDR. You will process hundreds of PBs and code mainly in Python and PySpark. You will be independent but surrounded by a large team of strong and experienced multi-disciplinary researchers

Partner with Product, Engineering and User Experience (UX) research teams to provide investigative thought leadership, support metrics research and advanced statistical analysis of user journeys across GIE surfaces and Google products
Identify metrics improvement areas, design new metrics, and evaluation methods
Perform large-scale data analysis and modeling to identify opportunities for deepening the understanding of end-user behavior, product improvements and measure the impact of initiatives on top level KPIs
Use statistical methods to design and suggest experiments and new ways to establish causality, estimate impact and answer strategic questions using data
Support teams with advanced experimentation methods, detect user learning effects, and drive actionable user insights. Make product recommendations with presentations of findings for multiple levels of stakeholders.

As a Senior Data Scientist, you will be part of a multidisciplinary AI team, working on AI-driven solutions in audio and text fields. You will apply machine learning and deep learning techniques, with a strong emphasis on Deep Learning for Time-Series Analysis, to develop scalable AI models that directly impact senior care. You will collaborate closely with R&D teams, leveraging real-world data to build high-performance AI solutions. This is an opportunity to tackle complex, real-world challenges, drive cutting-edge AI research, and develop innovative solutions tailored to the needs of caregivers and healthcare providersall within a dynamic, fast-paced environment.

Key Responsibilities:
Develop and optimize data pipelines and machine learning models, with a focus on Deep Learning for Time-Series Analysis.
Take ownership and lead end-to-end delivery, from innovation, experimentation, and research to full development and deployment to production.
Lead research initiatives to solve complex data science challenges, applying deep learning techniques.
Continuously monitor and refine model performance, ensuring high accuracy, efficiency, and reliability.
Work closely with Product, Business, and R&D teams to align AI innovations with company objectives.
Solve non-trivial, non-classical data science challenges using creative and outside-the-box thinking.
Work in a fast-paced startup environment, contributing to the development of cutting-edge AI-driven solutions.

We are looking for an experienced Data Scientist who can leverage and develop innovative machine learning, NLP, and generative AI technologies, for solving problems within a wide scope.

As a part of our Data Science group, you will work on highly complicated challenges, from research to production, and help shape our algorithms and AI platform. You will work with Developers, Analysts, Product Managers, and business owners on growth opportunities and new ideas.

You should have a strong background and experience in the machine learning pipeline through business understanding, research, data exploration, feature engineering, model building, performance evaluation, testing, production-level code and deployment, model monitoring, and maintenance.

What am I going to do?
Take leading roles in projects such as search engine ranking, promoted ads in search results, recommendations, users segmentation and personalization, online bidding optimization, text analysis, real-time predictions, live streaming data handling, exploration-exploitation problems, etc.
Work closely with various departments in the company to provide advanced Data Science solutions end to end.
Write and own production models and code.
Independent research and innovation in new content and technological domains.
Lead and advise other team members.
Continuously produce new initiatives and improvement ideas.
Act as a leader of AI platform. Develop models and framework solutions for the group.

We are looking for a Data Scientist- Autonomous.
The Research and Data Science department plays a pivotal role in our company, generating value by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more).
As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making.
What You'll Be Doing
Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities