דרושים » תוכנה » data Scientist בחברת סטארט-אפ

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 a deep learning engineer experienced with computer vision to join our DL algorithms Team.
We are dealing with a variety of tasks such as regression, segmentation, classification and detection while editing millions of images every week for professionals, and holding tens of millions edited images by professionals used as datasets.
Responsibilities
Design, development and bring to production novel, robust and efficient deep learning algorithms in the field of computer vision.
Create proofs of concept for new products and technology.
Evaluate and benchmark different algorithms for unique, proprietary datasets.
Collaborate with team members to define future technology and features.

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

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