דרושים » דאטה » Data Science Team Lead

In this role, you will lead a team of Machine Learning Scientists and Engineers dedicated to building, training, and deploying cutting-edge Generative AI models. This includes developing foundation models trained on our companys extensive textual data and creating fine-tuned models designed to tackle complex travel-related tasks. Your leadership will play a pivotal role in advancing the application of AI to transform the travel experience for millions of customers.
As a technical manager, you should be passionate about GenAI technology, keep up to date with recent breakthroughs in the field, define and shape the teams ML roadmap, and not be afraid to get your hands dirty with code when needed.
You are expected to be the focal point for all technical aspects, make sure your team members deliver on their tasks, and work together with other stakeholders to define and shape the roadmap of our products. You will work independently and will also be responsible for making technical decisions within your team.
When it comes to management, your expertise in handling people will motivate and inspire them to reach outstanding success! You should have experience in developing people. You will mentor and coach your team while working closely with a Product Manager.
Key Job Responsibilities and Duties:
Leadership in LLM Development- Build, Guide and mentor a team of ML scientists and ML engineers in the development, fine-tuning, and deployment of large language models (LLMs) tailored for the travel domain.
Expertise in the engineering aspects of deploying LLMs at scale with minimal latency. This includes optimizing model performance, scalability, and efficiency to meet the demands of real-time, high-traffic applications.
Define and communicate the technical vision and strategy for LLM-related initiatives, ensuring alignment with company goals and customer needs.
Foster a culture of collaboration, innovation, and excellence within the team.
Prioritize work in collaboration with Product Managers, depending on business needs and keeping stakeholders aligned at all times.
Translate machine learning vision and strategy into planning and execution, and ensure timely delivery of their plans.
Develop innovative ML models, algorithms, and engineering approaches or identify existing ones, with the potential to impact our business.
Design and execute applied research plans to understand, apply, test, evolve, and generalize these technologies into reusable frameworks.
Translate business problems into viable, reliable and robust ML and AI solutions, accounting for constraints of the production environment.
Monitor product health, performance and business impact and act accordingly when requirements are not met.
Identify underlying issues and opportunities across domains and situations that are not obviously related through application of structured thinking and logic.
Solve issues by applying methods and insights gained from a variety of disciplines, navigating a variety of environments.

Were seeking a visionary and technically hands-on AI Team Leader to join Alison.ai and take charge of driving innovation across our core AI systems. As the AI Team Leader, you'll guide the architecture and development of advanced machine learning models that power our video and creative analysis platform.
You will collaborate cross-functionally with product managers, engineering, and business development teams to deliver cutting-edge features that push the boundaries of whats possible in creative performance analysis.
This is a high-impact role for someone who thrives at the intersection of machine learning, product strategy, and creativity.
Key Responsibilities:
Lead the development, deployment, and optimization of machine learning models for video, image, and creative performance analysis.
Architect scalable AI/ML pipelines and infrastructure that support real-time and batch processing of multimedia data.
Guide research and experimentation initiativesidentify new technologies, modeling techniques, and opportunities for innovation.
Mentor and grow a team of machine learning engineers and data scientists as we scale.
Champion AI ethics, fairness, and explainability in our model development and deployment.
Stay ahead of industry trends in generative AI, computer vision, NLP, and Martech innovation, translating insights into competitive advantages.

The ML Detection team is a new, cross-functional team at the core of our product strategy. Its mission is to own and advance the machine learning-based validations that form the foundation of our accessibility testing solutions. This includes everything from data collection and research to deploying, monitoring, and maintaining models in production. You will lead a multidisciplinary team of Data Scientists, ML/Data Engineers, and Algorithm Developers to build foundational models and standalone validations that extend the reach and precision of our products, giving Evinced a critical competitive edge.

Your Impact:

Lead, mentor, and grow a multidisciplinary team of Data Scientists, ML Engineers, and Algorithm Developers, fostering a culture of trust, collaboration, and professional growth.
Own the end-to-end delivery of ML-based detection capabilities, from initial research and data collection to model deployment, monitoring, and algorithmic post-processing.
Provide hands-on leadership, actively contributing to technical solutions, architecture, and design reviews for new algorithms and models.
Collaborate closely with Product, DevOps, and R&D teams to align on priorities, manage integrations, and ensure efficient, impactful development cycles.
Architect and oversee the development of the infrastructure required for the entire ML lifecycle, including data management, experimentation platforms, and model deployment/monitoring systems.
Define and refine team processes, tools, and methodologies to optimize performance, quality, and stability, ensuring data science tasks have clear definitions of done.
Drive the strategic vision for the evolution of our detection capabilities, including UI patterns, interactive elements and accessibility issues, to meet current and future needs.
Act as the primary problem solver and technical resource for the team, guiding them through complex research and engineering challenges.

We are seeking a Senior Data Scientist who thrives on exploring complex data sets, extracting meaningful insights, and building high-quality, real-time data products to enhance our cutting-edge technologies. At Bigabid, we value talent and collaboration, fostering an environment where employees support one another to grow both individually and as a team. Our work is rewarding, challenging, and fun all while exceeding our clients expectations.

Responsibilities:

Deliver end-to-end machine learning models and impactful research.
Play a critical role in model development, prototyping, offline validation, production implementation, and online testing of our suite of ML products
Analyze vast and complex data sets to identify meaningful patterns and engineer features for ML models.
Design, build, tune, and interpret ML models by applying the scientific method and leveraging cutting-edge techniques.
Perform data manipulation, cleaning, validation, and cross-domain research to enrich insights and solutions.
Generate creative research ideas and actionable insights to address challenging business and technical problems.
Collaborate with product managers and engineering teams to align on problem definitions, trends, and solution opportunities.

We are looking for an experienced, sharp-minded and detail-oriented Data Scientist to join our growing R&D department, and work with an amazing team towards combating retail shrink - that is, catching thieves!
In this role you will develop and implement machine learning models and data-driven algorithms, create methodologies, and employ advanced data analysis techniques to define KPIs, measure our performance, and uncover actionable insights that drive impactful research. Your work will focus on transforming vast amounts of data into meaningful predictions, building scalable ML solutions, and enabling tools that improve the effectiveness of our innovative systems.
If you have a passion for data science and advanced analysis of systems solving real-world problems, wed love to hear from you!
A day in the life
Employ accurate data analysis techniques to evaluate system performance and identify areas for improvement. Produce clear, actionable insights to guide innovation and improve product KPIs.
Design and implement algorithms to automate and optimize performance measurement and decision-making processes.
Develop, train, and deploy predictive models that enhance our core capabilities.
Continuously monitor, validate, and refine models in production to ensure accuracy and robustness.
Collaborate with algorithm researchers, product managers, and Operations to align model design with business and R&D goals.

Required Senior Algo Data Engineer
Realize your potential by joining the leading performance-driven advertising company!
As a Senior Algo Data Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
About Algo platform:
The objective of the algo platform group is to own the existing algo platform (including health, stability, productivity and enablement), to facilitate and be involved in new platform experimentation within the algo craft and lead the platformization of the parts which should graduate into production scale. This includes support of ongoing ML projects while ensuring smooth operations and infrastructure reliability, owning a full set of capabilities, design and planning, implementation and production care.
The group has deep ties with both the algo craft as well as the infra group. The group reports to the infra department and has a dotted line reporting to the algo craft leadership.
The group serves as the professional authority when it comes to ML engineering and ML ops, serves as a focal point in a multidisciplinary team of algorithm researchers, product managers, and engineers and works with the most senior talent within the algo craft in order to achieve ML excellence.
How youll make an impact:
As a Senior Algo Data Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet
Our tech stack:
Java, Python, TensorFlow, Spark, Kafka, Cassandra, HDFS, vespa.ai, ElasticSearch, AirFlow, BigQuery, Google Cloud Platform, Kubernetes, Docker, git and Jenkins.

A day-to-day role as a Team Manager at our company includes:
Managing a multidisciplinary team of data engineers, data scientists, and data analysts.
Leading the development of advanced and creative solutions for complex technical challenges in areas like big data and machine learning.
Collaborating closely with data extraction, platform, and product teams.
Communicating with business stakeholders and gathering feedback from customers.
Hiring new team members and developing the groups structure.
Playing a crucial role in shaping product strategy within a startup-like environment.
Day-to-day, the team you will lead will:
Develop statistical and machine learning algorithms on large-scale data to estimate metrics, create features, and deliver insights.
Own end-to-end data processes and pipelines, from research and proof of concept to production.
Collaborate with product and R&D teams to plan and deliver best-in-class digital insights.
Design, validate, and monitor ongoing processes to ensure quality and reliability.
Identify, analyze, and monitor new raw data sources as needed.

gTech Ads is responsible for all support and media and technical services for customers big and small across our entire Ad products stack. We help our customers get the most out of our Ad and Publisher products and guide them when they need help. We provide a range of services from enabling better self help and in-product support, to providing better support through interactions, setting up accounts and implementing ad campaigns, and providing media solutions for customers business and marketing needs and providing complex technical and measurement solutions along with consultative support for our large customers. These solutions range from bespoke and customized ones for our customers to scalable support for millions of customers worldwide. Based on the evolving needs of our ads customers, we partner with Sales, Product and Engineering teams within our company to develop better solutions, tools, and services to improve our products and enhance our client experience. As a cross-functional and global team, we ensure our customers get the best return on investment with our company and we remain a trusted partner.
The gTech Ads Data Science EMEA team helps measure and optimize marketing ROI for our companys largest clients. We build bespoke models that address clients key business issues.
In this role, you will be responsible for applying best data science practices to solve our ads customers problems in marketing. You will be passionate about bringing the best of our companys Machine Learning (ML) capabilities to build innovative solutions that address our customer's problem-space. You will be responsible for executing on gTechs strategy and goal to deliver applied data science to our company's largest ads customers.
Responsibilities
Lead data science aspects of client engagements in the area of marketing effectiveness and marketing portfolio management with Machine Learning and statistics.
Collaborate with customers to unpack their problems and identify the best statistical techniques that can solve the problem; own the development of a modeling framework.
Engage important stakeholders to assess data and model readiness and be able to scale a proof-of-concept to a larger solution, collaborate with Product/Engineering teams to increase and optimize capabilities of our data scientist (DS) team, employing methods which create opportunities for scale, proactively helping to drive innovation.
Work with customer and internal teams to translate data and model results into tactical and insights that are actionable for decision.
Develop comprehensive understanding of our company data structures, and metrics, advocating for product changes where needed.

We are looking for a Machine Learning Tech Lead to promote machine learning engineering excellence. Someone who is passionate about building scalable, high-quality data products and processes, while ensuring production systems maintain strong real-time performance observability.

As a Tech Lead on the ML team , you will focus on designing and maintaining the core infrastructure that empowers the Machine Learning Engineers working within Data Science product teams. Youll collaborate closely with stakeholders across data science, product, and engineering, playing a pivotal role in driving the business by architecting and enabling the infrastructure for machine learning model development, serving, and lifecycle managementthe foundation of our product.

Responsibilities:

Partner with MLEs in Data Science product teams and key stakeholders to design and maintain infrastructure for:
Data wrangling supporting and enabling data requirements for research, training, validation, and testing.
End-to-end ML delivery enabling model performance development, training, validation, testing, and version control.
Drive engineering best practices including code and model versioning, CI/CD pipelines, rollout strategies, and disaster recovery procedures.
Build and support monitoring and observability tools dashboards, alerts, and performance tracking of models in production.
Lead architecture projects such as:
Feature Store centralizing feature engineering and serving across teams.
Vector Databases enabling large-scale embedding storage and retrieval for advanced ML applications.
GPU Cluster Scaling optimizing distributed training and inference infrastructure.
Collaborate with product, data science, and engineering teams to solve complex problems, identify trends, and create opportunities through robust ML infrastructure.

we are looking for a AI Engineer to join our R&D organization and help lead the development of AI-powered and data-driven capabilities in our Developer Productivity Platform.
In this role, you will transform data into actionable insights and intelligent models that help software teams understand, measure, and improve how they work. Youll work closely with product, data, and engineering teams to design and deliver AI and data science solutions that have real impact on developer productivity and business outcomes.

Key Responsibilities:
Design, develop, and deploy AI-driven features & data science and ML models to analyze code flows, software development processes, team behaviors, and performance metrics.
Build AI & data pipelines and analytical infrastructure that ensure data quality, accessibility, and freshness at scale.
Translate complex data into clear, actionable insights and code analysis that influence product direction and drive customer value.
Develop and maintain predictive, prescriptive, and diagnostic models to support use cases like delivery forecasting, productivity measurement, and team health analysis.
Partner with Product Managers, Data Engineers, and Backend Engineers to bring insights to life through AI & data-driven features and platform improvements.
Monitor and continuously improve model performance through experimentation, A/B testing, and user feedback loops.
Research and evaluate new AI/ML tools and methodologies to enhance the platforms intelligence and scalability.