We are looking for a passionate Senior Data Scientist, to work end to end on some of our core problems. Solving these will help drive revenue and improve decision making.
As a Full Stack Data Scientist you will be handed with a business problem and will be asked to provide an end to end solution - Unpack and thoroughly understand the business problem, define the strategy to deal with it and develop & deploy your solution along with relevant support.

What you'll be doing:
Design and implement end-to-end solutions from business needs all the way to live deployment.
Monitor and own models in production.
Model, design, and implement machine learning and data mining algorithms
Perform deep data analysis to evaluate performance and recommend improvements.
Help, guide and support our business partners to allow for scale and accuracy while adopting your solutions.

We are looking for a Senior Data Scientist.
The 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

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.

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.

Required Senior Data Scientist
Job Description
What will you do:
As Senior Data scientist, you will shape the future of identity security and develop innovative AI/ML solutions that enhance security and protect the emerging agentic AI landscape in top organizations. Drive AI research and engineering to address evolving threats and protect critical digital assets effectively.
Drive AI/ML projects from research to production, leveraging advanced algorithms, LLMs, classification models, Unsupervised learning and optimization techniques to enhance cybersecurity solutions.
Model Building: Design, implement, and optimize machine learning models, including deep learning, using frameworks such as PyTorch, TensorFlow, Hugging Face, and scikit-learn.
Work closely with product manager, engineers, software architects and analysts to understand requirements, validate model assumptions, and deliver actionable insights.
Identify AI/ML impact opportunities and translate business needs into actionable roadmap items.
Stay current with the latest advancements in data science and apply best practices to ensure optimal performance.