לוח משרות דרושים Senior Data Scientist משרה מלאה

We are seeking a Senior Data Scientist to be one of the first data science hires for our newly formed ML team. This is a unique ground-floor opportunity to build our data science capabilities from scratch and have direct influence on our analytical and modeling approaches. This role combines advanced data science expertise with foundational contributions, requiring someone who can develop sophisticated models, conduct deep analytical research, and help establish the data science methodologies that will guide the team as we scale. As one of our founding data scientists, you'll work closely with our Tech Lead to shape our modeling approaches, define our analytical standards, and build the fundamental data science skill set for future hires.
What You'll Do:
Build foundational data science capabilities: As one of our first data science hires, work with the Tech Lead to develop core modeling methodologies, analytical frameworks, and research practices
End-to-end model development: Take ownership of complete ML model lifecycle - from initial research and experimentation through production deployment and monitoring
Build impactful models: Design, develop, and deploy machine learning models that solve complex business problems across payments, risk, and customer analytics
Define analytical standards: Help establish best practices for data exploration, feature engineering, model validation, and statistical analysis
Conduct deep research: Lead exploratory data analysis and research initiatives to uncover insights and identify ML opportunities across the business
Partner with stakeholders: Work closely with business teams to understand requirements, translate problems into data science solutions, and communicate findings effectively
Establish model development practices: Help set up our approach to model experimentation, A/B testing, and performance monitoring
Shape data science culture: Contribute to establishing the team's analytical rigor, documentation standards, and knowledge-sharing practices
Drive innovation: Research and evaluate new ML techniques, algorithms, and approaches that could benefit our business use cases.

Were seeking a passionate Senior Data Scientist to join our AI team. With a wide array of responsibilities and corresponding impact, youll help spearhead our new product offering and the world-class AI conversation product impacting millions of patients.
Responsibilities:
Design, develop, and drive design processes and products that incorporate Generative AI (LLMs), models and knowledge Retrieval in order to help patients across the US.
Design and define data pipelines and evaluation pipelines.
Build applicative AI in production on a large scale.
Build solutions for different mediums, including voice products with minimal latency and high accuracy.
Provide a scientific evaluation of the quality of our models..
Continuously improve our existing NLP capabilities to help patients across the US answer any question, schedule appointments with their doctor, refill their prescriptions, and much more.
Use best practices and SOTA from the AI industry, but also push the envelope to new heights.

We are looking for a Data Science / Machine Learning Engineer Tech Lead to join the data science group. Youll have the opportunity to make a significant impact by creating products that are used by millions of users around the world.
Our Data Science group is responsible for developing and implementing data-driven models, conducting research to evaluate new data science methodologies, and analyzing large datasets to extract actionable insights.
The individual will collaborate with cross-functional teams to ensure actual impact on our users and business outcomes.
Responsibilities:
Machine Learning: Design, Research, analyze, develop, and implement predictive models, from inception to production, in addition to MLOps infra for various of machine learning techniques to address complex business problems.
Code review to peers, maintain code quality, unit testing, E2E testing, ML models monitoring, maintainability and scalability
Collaboration: Work closely with cross-functional teams including Devops, Back End, and Mobile teams to define project goals and deliver data-science projects into production.
Stay updated with the latest research and advancements in AI.
Reporting: Create clear, concise, and actionable reports to communicate insights to stakeholders.

We are looking for a passionate Senior Data Scientist to join our all-star team.
This is an amazing opportunity to join a multi-disciplinary A-team while working in a fast-paced, results, marketing and data-oriented environment.
If you are experienced but still hungry to learn and impact - wed love to have you on our team!
What You'll Do:
Devise, initiate, manage and execute cutting edge exploration and exploitation projects.
Apply your knowledge of Data Science and algorithm development to create data solutions.
Analyze extremely large (petabytes) and diverse datasets to solve complex problems, and then develop algorithmic solutions to do it for you.
Proactively seek growth opportunities aligned with core KPIs.
Partner with other functions in the company, to support decision making.
Instant data gratification guaranteed!.

As a customer-centric tech company, we created an insurance experience that is smart, instant, and delightful.

youll be working with a group of like-minded makers, who get a kick out of moving fast and delivering great products. We surround ourselves with some of the smartest, most motivated, creative people who are filled with positive energy and good karma.

Unlike most publicly traded companies, were nimble and efficient. We take pride in the fact that we still think and operate like a startup. We dont care much about titles and hierarchy and instead focus on innovation, bold moves, and challenging the status quo.

Were built as a lean, data-driven organization that relies on a common understating of objectives and goals to provide teams with autonomy and ownership. We dont like spending our days in meetings and we skip committees altogether. theres no such thing as going over someones head. We have zero tolerance for bureaucracy, office politics, and lean-back personalities.

As a Public Benefit Corporation and a certified B-Corp, we deliver environmental and social impact using our products and tech. Through our Giveback program, we partner with organizations such as the ACLU, New Story, The Humane Society, Malala Fund, American Red Cross, 360.org, charity: water, and dozens of others, and have donated millions towards reforestation, education, animal rights, LGBTQ+ causes, access to water, and more.
What youre applying for
As part of the Data Infrastructure group, youll help build data platform for our growing stack of products, customers, and microservices.
We ingest our data from our operational DBs, telematics devices, and more, working with several data types (both structured and unstructured). Our challenge is to provide building tools and infrastructure to empower other teams leveraging data-mesh concepts.
In this role youll
Help build data platform, designing and implementing data solutions for all application requirements in a distributed microservices environment
Build data-platform ingestion layers using streaming ETLs and Change Data Capture
Implement pipelines and scheduling infrastructures
Ensure compliance, data-quality monitoring, and data governance on data platform
Implement large-scale batch and streaming pipelines with data processing frameworks
Collaborate with other Data Engineers, Developers, BI Engineers, ML Engineers, Data Scientists, Analysts and Product managers
Share knowledge with other team members and promote engineering standards

Join our Data Science research team, leveraging analytical capabilities into the field of cybersecurity.
Responsibilities
Develop and implement statistical models and algorithms in big data environment to analyze communication data and logs for endpoint devices, identifying network attacks and anomalies.
Extract insights and enrichment using advanced analytical tools.
Lead end-to-end data science projects, including requirements gathering, conducting proof of concept (POCs), demonstrating value, building pipelines in operational systems and monitoring project progress.
Maintenance, improvement and optimization of production models.
Collaborate with various stakeholders within the unit and identify challenges and improvements that can addressed using data science techniques.