As a Machine Learning Engineer at MyHeritage, you will play a crucial role in developing and implementing machine learning models that drive our products and user experiences. You will have a significant impact on our large and growing user base by leveraging the latest AI technologies to solve challenging problems at scale. This is a unique opportunity to join a forward-thinking team that is passionate about innovation, data, and machine learning.

What you’ll do

• Design, develop, and deploy machine learning models for various business needs.
• Collaborate with cross-functional teams, product managers, and software engineers, to integrate ML solutions into production systems.
• Experiment with and iterate on model architectures to improve accuracy, efficiency, and scalability.
• Work with large datasets to preprocess, clean, and extract meaningful features for model training.
• Utilize MLOps best practices to automate and streamline the development lifecycle of ML models.
• Monitor model performance and fine-tune for optimization.
• Stay updated with the latest research and advancements in machine learning and AI.

What you bring

Technical skills:

• Strong foundation in machine learning techniques such as supervised and unsupervised learning, deep learning, and vision/NLP experience.
• Proficiency in Python, along with popular ML libraries and frameworks such as PyTorch, Scikit-Learn, pandas, NumPy, SciPy, TensorFlow.
• Experience with data preprocessing and feature engineering for structured and unstructured data.
• Knowledge of model deployment and serving, using tools like Docker, Kubernetes, or cloud-based services (AWS, GCP, Azure).
• Familiarity with MLOps tools for automation and monitoring (e.g., MLFlow, ClearML).
• Experience with SQL for data extraction and analysis (optional).

Experience:

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field.
• 7+ years of experience in software development, including at least 3 years of experience in the machine learning domains.
• Experience working in a B2C company or a similar high-paced environment is an advantage.
• Proven track record of implementing impactful machine learning solutions in production.

Core attributes

• Strong analytical mindset, with the ability to tackle complex problems with creativity and efficiency.
• Excellent communication skills for conveying technical ideas to both technical and non-technical stakeholders.
• High level of attention to detail and quality in your work.
• Ability to work effectively in a team environment, while also being a self-starter when working independently.
• Curious and eager to keep learning about the latest trends in AI and machine learning.
• Comfortable in a fast-paced, dynamic work environment with changing priorities.

 About MyHeritage

MyHeritage is the leading global discovery platform for exploring family history. With billions of historical records and family tree profiles, and with sophisticated matching technologies that work across all its assets, MyHeritage gives users the joy of discovering their past and empowering their future. MyHeritage is the most popular DNA test and family history service in Europe. Since 2020, MyHeritage is also home to the world’s most advanced AI technologies for repairing, enhancing, colorizing, and animating historical photos. Learn more at www.myheritage.com. See what it’s like to work at MyHeritage on www.glassdoor.com.

Benefits at MyHeritage

Our employees enjoy a range of benefits to enhance work-life balance and well-being:

• Hybrid work model
• Modern, beautiful office in Or Yehuda with shuttle service from Tel Aviv and employee parking (for our Or Yehuda employees)
• On-site gym and pilates classes
• Dog-friendly office
• Well-stocked kitchens and a monthly meal allowance 
• Fully funded supplemental health insurance

#LI-Hybrid

The role

Nebius is looking for a Senior Data Scientist to build and deploy time series forecasting and classical machine learning models that support core business planning and operational decisions. You will own problems end-to-end, from data exploration and feature engineering to model deployment and monitoring, working with large-scale, real-world datasets.

The role emphasizes strong statistical thinking, robust modeling, and production reliability over experimentation with trendy frameworks. Your work will directly impact forecasting accuracy, resource planning, and key business metrics.

You’re welcome to work in our offices in Tel Aviv.

Your responsibilities will include: 

• Time series forecasting. Design, build, and maintain forecasting models (e.g., demand, usage, capacity). Evaluate performance using appropriate metrics and improve accuracy over time.
• Classical ML modeling. Develop and deploy models using regression,Binary classifcatiom ,  tree-based methods, and other well-established approaches where they provide the best trade-off between performance, interpretability, and maintainability.
• Feature engineering & data preparation. Build robust pipelines for data cleaning, transformation, and feature generation (including time-based features, seasonality, and external signals).
• Model evaluation & monitoring.Define evaluation frameworks, backtesting strategies, and monitoring to ensure models remain stable and reliable in production.
• Production & MLOps. Deploy models into production environments, collaborate on pipeline orchestration, and ensure reproducibility and version control.
• Exploratory analysis. Analyze large datasets to identify patterns, anomalies, and drivers of change in time-dependent behavior.
• Stakeholder collaboration. Work closely with business and product teams to define forecasting needs, align on success metrics, and translate model outputs into actionable insights.
• Cross-domain contribution. Contribute to adjacent data science areas (e.g., LLM-based systems) as needed, ensuring shared ownership and continuity across team responsibilities.

We expect you to have: 

• Experience as a data scientist working in production environments (5+ years).
• Experience with time series modeling and forecasting techniques.
• Experience building reliable data pipelines and working with large datasets.
• Experience with modern data science tools and ecosystems using Python (e.g., NumPy, Pandas, Scikit-learn, deep learning frameworks).
• Strong SQL skills and experience working with large datasets.
• Strong foundation in statistics and machine learning fundamentals.
• Background in Computer Science, Statistics, Mathematics, Industrial Engineering, Economics, or a related field (Master’s degree or equivalent).
• Demonstrated ability to take models from idea to production and ensure ongoing value.
• Demonstrated ability to apply structured thinking and robust evaluation in forecasting problems.
• Strong communication skills and ability to explain model outputs, uncertainty, and limitations.
• Working knowledge of spoken and written English.

It will be an added bonus if you have: 

• Experience working in cloud environments (preferably Azure).
• Experience with MLOps tools and production model lifecycle management.
• Experience with workflow orchestration tools such as Apache Airflow.
• Familiarity with LLM-based systems (e.g., evaluation, RAG pipelines) in applied settings.

Job Description

Astera labs is seeking a skilled and motivated Data Scientist. This individual will play a pivotal role in identifying key data points for collection, developing strategies to accumulate data and deriving actionable insights an anomaly based on a solid foundation of relevant know-how. Also, will also be responsible for creating, testing, and deploying scripts and methods for data collection and analysis to support decision-making. The Engineer will collaborate with cross-functional teams to identify critical data sources to determine the most effective data collection strategies, will develop automated and scalable data collection pipelines, will ensure data quality, integrity, and consistency across all sources and may use AI techniques to refine the results toward failures predictions.

Basic Qualifications

• Bachelor’s degree in computer science, Data Science, Engineering, Mathematics, or a related field.
• Advanced degrees in data science or Machine learning / AI - Advance.
• Proficiency in programming languages such as Python, R, or MATLAB.
• Strong understanding of data manipulation and analysis tools (e.g., Pandas, NumPy, SQL).
• Understanding of high speed interfaces such as Ethernet, PCI-E , WiFi.
• Experience with data visualization tools such as Tableau, Matplotlib, Graphana.
• Strong analytical and critical-thinking skills to identify patterns and outliers.
• Customer-obsession, Think and act with the customer in mind!
• Goal-driven, Self-motivated, be able to work independently and with teams with people around the globe.
• Entrepreneurial, open-minded behavior and can-do attitude.

Required Experience

• Experience with data manipulation and analysis tools (e.g., Pandas, NumPy, SQL).
• Machine learning and AI techniques and frameworks (e.g., TensorFlow, Scikit-learn).
• Proven ability to manage multiple tasks and meet deadlines.

Preferred Experience

• Embedded Firmware development with C-language, scripting with Python or other equivalent programming languages.
• Master’s degree in a relevant field.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) for data storage and processing.
• Familiarity with big data technologies (e.g., Hadoop, Spark).
• Knowledge of engineering design tools and processes.

What Do We Do?

Triple Whale is the complete intelligence platform for ecommerce, helping brands stop guessing and start knowing what’s actually driving growth, what’s wasting money, and what to do next — with total confidence. By pulling all of a company’s data into one place, delivering measurement tools teams can actually trust, and applying the smartest AI in the industry, Triple Whale turns fragmented data into clear insights and actionable recommendations. That intelligence can then be put to work through AI agents and automations that generate creative assets, take action across marketing channels, and make every tool in their stack smarter and more effective.

More than 60,000 ecommerce brands including Pressed Juicery, OUAI, and True Classic trust Triple Whale to grow faster and drive revenue with fewer resources by uncovering opportunities and acting on them at a scale that would be impossible manually.

Why Triple Whale Needs You:

We’ve reached a strong product–market fit and are scaling rapidly — which means marketing measurement, experimentation, and optimization are becoming more complex and more critical than ever. As privacy changes, fragmented signals, and multi‑channel marketing continue to evolve, brands need sophisticated, production‑grade marketing science they can actually trust.

We’re looking for an Applied Data Scientist to help us build and scale the core marketing science products that power our platform. This role sits at the intersection of data science and engineering: owning statistical models end to end, deploying them into production, and turning advanced analytics into reliable, customer‑facing capabilities. Your work will directly influence how thousands of brands measure ROI and allocate millions in marketing spend.

What You’ll Do:

• Build marketing measurement and optimization products (e.g., attribution models, MMM, incrementality testing, forecasting systems)
• Develop and deploy statistical and machine learning models to production
• Create scalable data pipelines and APIs that serve real-time analytics
• Partner closely with Product, Engineering, and other stakeholders to translate business questions into clear analytical solutions.
• Own features end to end from statistical design and validation through deployment, monitoring, and iteration.

What You’ll Bring:

• 4–7 years of experience in applied data science
• Ability to work from our Jerusalem office (located in the Central Bus Station next to the train) 2 times a week (Monday & Wednesday) is required
• Strong Python skills (pandas, scikit-learn, statistical libraries)
• Experience deploying models to production (not just notebooks)
• Solid statistics and machine learning fundamentals
• SQL and database experience
• Experience in building APIs or backend services
• Bachelor's or Master's in a quantitative field (Statistics, CS, Math, Machine Learning/Data Science)
• Strong English communication skills with technical and non-technical audiences
• Self-starter comfortable with ambiguity and autonomy

Bonus Points If You Bring:

• Marketing analytics background (attribution, experimentation, measurement)
• Bayesian statistics or causal inference experience
• Cloud platform knowledge (GCP, AWS, or Azure)
• Time series analysis and forecasting

Why You’ll Love This Role:

This role offers true end‑to‑end ownership from statistical design to production deployment and real customer impact. It’s not pure modeling and not pure engineering, but a blend of both, focused on solving real marketing problems at scale. You’ll work on high‑impact systems that directly shape how businesses understand performance and invest their budgets, all within a fast‑moving, product‑driven environment where your work ships quickly and matters immediately.

Our Values

• We Are Customer Obsessed: From our mission to every detailed project, everything we do is designed to create a positive impact for our customers.
• We Move (Very!) Quickly: The speed at which we work, iterate, and deliver value is our most competitive advantage. 
• We Are Trustworthy: Candor, directness, and honest communication helps us learn, grow and improve so we can win together. 
• We Are Curious: We extend beyond our comfort zone and ask questions that guide us towards new, creative, and bold paths.
• We Act Like A Mensch: We act with honor, integrity and empathy, and have deep respect for our customers and each other.

Join Us in Making Waves

If you’re looking for more than just a job and want to be part of a movement reshaping the future of Ecommerce, Triple Whale is the place for you. We’re on the lookout for driven, curious, and creative individuals ready to thrive in a fast-paced environment.

Triple Whale is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.Referred?  Got here thanks to a friend? Splash some gratitude their way!  They'll need to submit your application through our referral system to make it official.

About QuantHealth

QuantHealth is a growing AI startup in the clinical trial space, leveraging AI, biomedical data, knowledge graphs, and real-world patient data to simulate and optimize clinical trials for pharmaceutical companies. Our platform combines large-scale biomedical knowledge, clinical trial data, and patient-level data to help customers simulate clinical trials, reduce development risk and cost, shorten timelines, and improve the probability of clinical trial success.

About the Role

As a Data Scientist in the CDS R&D team, you will play a key role in researching, developing, and productionizing advanced data science solutions that power QuantHealth’s clinical simulation and prediction capabilities.

This role is designed for a strong applied data scientist who enjoys solving complex, ambiguous problems end-to-end: from data exploration and feature engineering, through model development and validation, to building scalable pipelines and AI-driven workflows. You will work closely with clinical experts, product, delivery, engineering, and other data science teams to translate challenging clinical and biomedical questions into robust data-driven solutions.

The ideal candidate brings several years of hands-on experience in applied data science, machine learning, and data pipeline development. Additional qualities we look at in candidates are scientific thinking, project ownership, and the ability to independently learn and operate in complex domains. Experience with biomedical or clinical data is a strong advantage.

This position involves working with a modern Python-based data science stack, building predictive models, developing data and ML pipelines, and contributing to the continuous improvement of QuantHealth’s clinical trial simulation product. The role requires curiosity, strong self-learning abilities, research orientation, and rigorous analytical thinking.

Responsibilities

• Design, develop, and validate data science models, algorithms, and tools that support QuantHealth’s internal and customer-facing clinical simulation products.
• Build end-to-end data science solutions, including data ingestion, feature engineering, model development, evaluation, and deployment-ready pipelines.
• Collaborate with clinical, product, delivery, engineering, and data science teams to prototype and implement data-driven solutions.
• Explore, process, and integrate diverse data sources, including clinical trial data, EHR/RWD, biomedical literature, biomedical ontologies, and knowledge graphs.
• Develop scalable ETL and data pipelines to support automated clinical simulation workflows.
• Build LLM-based and agentic systems to automate internal research, data processing, and biomedical reasoning workflows.
• Develop and improve data projects using tools such as PySpark, PyTorch, PyGeometric, MLflow, SQL, and the broader Python data stack.
• Stay current with emerging methodologies in machine learning, LLMs, knowledge graphs, biomedical AI, and applied data science.
• Contribute to internal knowledge sharing, best practices, and scientific discussions within the R&D organization.

Qualifications

• MSc or PhD in data science, computer science, computational biology, or a related quantitative field.
• 4+ years of hands-on experience in applied data science, machine learning, or algorithm development.
• Strong Python skills and practical experience with common data science and ML libraries such as pandas, NumPy, scikit-learn, PyTorch, SQL, and Spark.
• Proven experience building end-to-end data science solutions, from raw data processing to model development, evaluation, and implementation.
• Experience working with large, messy, real-world datasets and transforming them into reliable analytical or machine learning pipelines.
• Strong understanding of machine learning concepts, model evaluation, statistical analysis, and experimental design.
• Experience with cloud-based computing environments and scalable data processing pipelines.
• Strong analytical and problem-solving skills, with attention to details and scientific rigor.
• Strong research mindset and ability to independently learn new domains, methods, and technologies.
• Excellent communication skills and ability to collaborate effectively across clinical, product, engineering, and data science teams.

Strong Advantages

• Experience working with biomedical, healthcare (RWD/EHR), pharmaceutical, biomedical ontologies, or real-world patient data.
• Experience developing LLM-based workflows or agentic pipelines.
• Experience with knowledge graphs, graph embeddings, GNNs, or graph-based ML.
• Experience with PySpark, PyTorch, PyGeometric, MLflow, or similar ML engineering tools.
• Experience creating interactive data applications, dashboards, or internal tools.
• Familiarity with clinical trial design, drug development, computational/system biology, or translational medicine.

Who we are

DV is the leader in digital performance solutions, helping our advertiser and agency partners verify the quality of their digital campaigns, Optimise to improve performance and Prove that they’re achieving their business outcomes, through unbiased 3rd party data and analytics. DV’s mission is to be the definitive source of transparency and data-driven insights into the quality and effectiveness of digital advertising for the world’s largest brands, agencies, publishers, and digital ad platforms.  Since 2008, DV has helped hundreds of Fortune 500 companies gain the most from their media spend by delivering best-in-class solutions across the digital advertising ecosystem, helping to build a better industry. Learn more at www.doubleverify.com.

What you will do

You will lead a team of experienced Data Scientists while remaining deeply involved in the technical work.

This is a hands-on leadership role (~70% hands-on) combining direct modeling work with ownership of team direction and execution.

You will work on core systems that operate at a massive scale, where:

• Data is abundant, but labels are scarce and expensive

• problems are long-tail and ambiguous

• Systems must meet strict latency and cost constraints (pre-bid)

Your responsibilities include:

• Lead development of content classification systems across social platforms (Meta, TikTok, YouTube), web, and apps

• Design and build models across computer vision, NLP, and multimodal pipelines

• Own the full lifecycle: data selection -> labeling strategy -> training -> evaluation -> deployment

• Develop strategies for efficient data curation and labeling (active learning, auto-labeling, sampling under scale)

• Improve model quality (precision/recall) while balancing cost, latency, and scale

• Drive automation systems (auto-labeling, auto-curation, retraining loops)

• Apply modern AI approaches (LLMs, embeddings, foundation models) to real production problems

• Lead and mentor a team of senior Data Scientists, setting technical direction and pushing execution forward

• Work closely with ML Engineering, Product, and Policy to translate ambiguous requirements into scalable systems

Who you are

• 3+ years of experience leading Data Science / ML teams

• 6+ years of hands-on experience in Machine Learning / Deep Learning

• Strong background in Computer Vision and/or NLP

• Experience building and deploying production ML systems at scale

• Strong understanding of real-world trade-offs (accuracy, cost, latency)

Technical requirements

• Hands-on experience with deep learning frameworks (PyTorch / TensorFlow)

• Experience with ML/DS tools (scikit-learn, OpenCV, HuggingFace, etc.)

• Experience working with large datasets and model evaluation pipelines

Advantages

• Experience with multimodal systems (vision + text + audio)

• Experience with LLMs / embeddings / foundation models

• Experience with AutoML, active learning, or data-centric AI

#Hybrid#
 

About Pagaya

Pagaya is a global technology company making life-changing financial products and services available to more people nationwide, as it reshapes the financial services ecosystem. By using machine learning, a vast data network and a sophisticated AI-driven approach, Pagaya provides comprehensive consumer credit and residential real estate solutions for its partners, their customers, and investors. Its proprietary API and capital solutions integrate into its network of partners to deliver seamless user experiences and greater access to the mainstream economy. Pagaya has offices in New York and Tel Aviv. For more information, visit pagaya.com.

About the Role

Pagaya is seeking an experienced data scientist to join our Model Validation team. The ideal candidate will bring a blend of data science knowledge and analytical skills, understanding in Finance and an understanding of the regulatory landscape of credit lending. As a core team member, you will work closely with model developers to assess model performance, data quality, conceptual soundness, and produce thorough, compliant documentation for regulatory review, ensuring our models meet the highest standards. You will be required to challenge the models, helping Pagaya deliver high-quality validated models for loan pricing and underwriting.

Key Responsibilities:

• Conduct thorough validation of ML models to assess performance, data quality, robustness, conceptual soundness, regulatory requirements and more
• Conduct independent tests to assess performance and limitations, and establish model assumptions
• Suggest and develop alternative models to challenge and improve existing models
• Provide insights into the' strengths and weaknesses of models in terms of Data Science methodology and Finance as well as recommend practical solutions.
• Prepare comprehensive validation documentation
• Support the ongoing monitoring and improvement of existing predictive models
• Stay updated on the latest research in ML credit risk modeling and financial news, ensuring that our practices align with industry standards

Required Qualifications:

• 3+ years of experience in Data Science roles with experience with ML models- Must
• Work experience in a financial company
• Python - experience with data science packages (pandas, numpy,  sklearn, seaborn)
• Bachelor's degree in Data Science, Statistics, Computer Science, or a related quantitative field
• Excellent problem-solving skills with the ability to think critically and creatively
• Strong communication skills and the ability to work effectively in a collaborative team environment
• Fluent in English, both verbal and written

Preferred Qualifications:

• Masters degree
• Experience in Finance, specifically with financial data or models - advantage
• Experience with cloud platforms (e.g., AWS) and distributed computing
• Familiarity with regulatory compliance requirements for financial models (e.g., SR 11-7)

Our Team

Pagaya was founded in 2016 by seasoned research, finance, and technology entrepreneurs, and we are now 500+ strong in New York, Los Angeles, and Tel Aviv.

We move fast and smart, identifying new opportunities and building end-to-end solutions from AI models and unique data sources. Every Pagaya team member is solving new and exciting challenges every day in a culture based on partnership, collaboration, and community.

Join a team of builders who are working every day to enable better outcomes for our partners and their customers.

Our Values

Our values are at the heart of everything we do. We believe great solutions are built through a great community.

• Advance Inclusion- We create a world where everyone can win, designing systems that better represent people and generate sustainable value for our employees, partners and investors.
• Be Accountable Together- We proudly own our actions and our results, taking initiative to ensure our work gets over the finish line as a team.
• Continuously Learn- We challenge ourselves for the sake of getting better as individuals, as teams, and as an organization to deliver for our partners.
• Debate and Commit- We respectfully and openly debate to strengthen our ideas and build shared conviction - once we decide, we go all in, together.
• Dream Big and Act- We boldly tackle complex problems, pressure-test solutions in real-time, and adapt with speed and energy.

More than just a job

We believe health, happiness, and productivity go hand-in-hand. That's why we're continually looking to enhance the ways we support you with benefits programs and perks that allow every Pagayan to do the best work of their life. 

Pagaya is an equal opportunity employer. Pagaya is encouraging diversity and actively seeking applicants from all backgrounds, as are committed to creating a diverse workforce together with an inclusive environment for all. Employment is decided on the basis of qualifications, skills, and business needs.

Pagaya is an equal opportunity employer. Pagaya is encouraging diversity and actively seeking applicants from all backgrounds, as are committed to creating a diverse workforce together with an inclusive environment for all. Employment is decided on the basis of qualifications, skills, and business needs.

The opportunity
Join a high-impact ML team building state-of-the-art systems that optimize experiences for billions of users. You'll tackle challenging problems across diverse datasets - with the freedom to explore novel approaches and infrastructure to deploy them at scale.

What Success Looks Like:

Short-term: Ship your first production model with measurable impact within 3 months.

Long-term: Own major ML initiatives end-to-end and introduce new methodologies that expand the team's capabilities.

Your Impact:

Elevate our technical bar with fresh ML perspectives. Shape our roadmap by identifying opportunities others miss. Your research skills keep us cutting-edge while your execution speed drives results.

What You'll Gain:

Work on real-time ML systems at scale with rich, diverse data

Autonomy to define problems and drive projects from idea to impact

Freedom to explore emerging techniques and expand your scope

Fast feedback loops through strong experimentation infrastructure

What you'll be doing

• Join a high-impact ML team building state-of-the-art systems that optimize experiences for billions of users. You'll tackle challenging problems across diverse datasets - with the freedom to explore novel approaches and infrastructure to deploy them at scale.
• What Success Looks Like:
• Short-term: Ship your first production model with measurable impact within 3 months.
• Long-term: Own major ML initiatives end-to-end and introduce new methodologies that expand the team's capabilities.
• Your Impact:
• Elevate our technical bar with fresh ML perspectives. Shape our roadmap by identifying opportunities others miss. Your research skills keep us cutting-edge while your execution speed drives results.
• What You'll Gain:
• Work on real-time ML systems at scale with rich, diverse data
• Autonomy to define problems and drive projects from idea to impact
• Freedom to explore emerging techniques and expand your scope
• Fast feedback loops through strong experimentation infrastructure

What we're looking for

• Strong Deep Learning Expertise – Comprehensive knowledge of DL theory paired with the practical intuition gained from training many networks; comfortable working with SOTA pretrained models while understanding the underlying mechanics of convergence and scale.
• Proven ability to deliver production ML models with measurable business impact - from problem definition through A/B testing -> deployment and outcome tracking
• AI-Native Builder Mentality – Comfortable breaking conventional development cycles to build fast and ship often. You have a deep mastery of the modern GenAI stack for development, using it to automate the mundane and focus your cognitive load on high-level architecture and model performance.
• Strong programming skills in Python and Deep Learning stack (PyTorch, scikit-learn, XGBoost) with ability to write clean, efficient code for production systems
• Self-directed research capability - demonstrated ability to independently explore unfamiliar ML domains, synthesize technical literature, and implement novel approaches
• Structured problem-solving methodology - ability to decompose complex business problems, design solution approaches, and communicate technical findings to stakeholders

You might also have

• Positivity and enthusiasm

Additional information

• Relocation support is not available for this position
• Work visa/immigration sponsorship is not available for this position

Benefits
At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.

Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.

While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program

Life at Unity
Unity [NYSE: U] is the world’s leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D — closing the gap between ideas and reality. For more information, please visit www.unity.com.

Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.

Your privacy is important to us. Please take a moment to review our Prospect Privacy Policy and Applicant Privacy Policy. Should you have any concerns about your privacy, please contact us at DPO@unity.com.

#SEN

The Data Science role at Armis is the engine behind our industry-leading Exposure Management (EM) platform.
You will be responsible for the AI models that power our CAASM (Cyber Asset Attack Surface Management) capabilities and our advanced Vulnerability Prioritization and Remediation engines.

We are building the intelligence layer that helps organizations implement a Continuous Threat Exposure Management (CTEM) framework. You will build models that normalize fragmented data from hundreds of sources, calculate complex risk scores, and prioritize which exposures actually pose a threat to the business.

We are looking for an experienced and creative data scientist, with a software development touch, to join our Data Science and Armis family. A data scientist that understands and loves data, and lots of it.

 What you will do...

• Solve Applied Product Challenges: Deep-dive into the Armis product ecosystem to identify and solve high-impact problems. You will translate complex customer needs into scalable ML features that directly improve the user experience.
• Lead Exposure Intelligence R&D: Develop features that unify asset data (CAASM) with threat intelligence. This includes building models for entity resolution (deduplicating assets across fragmented sources) and automated risk assessment.
• Advanced NLP & Knowledge Extraction: Use NLP and LLMs to parse unstructured security data—such as CVEs, threat intel feeds, and security advisories—to automate the mapping of vulnerabilities to specific business contexts.
• Predictive Prioritization: Design and optimize algorithms that go beyond static CVSS scores. You will incorporate exploitability (EPSS), reachability, and business criticality to help clients focus on the 1% of exposures that matter most.
• End-to-End Ownership: Work closely with Product Managers and Data analysts and Engineers to ensure your models aren't just accurate in a notebook, but are robust, explainable, and deliver clear value within the product UI.
• Graph-Based Attack Surface Mapping: Identify hidden patterns and relationships between assets, users, and vulnerabilities to visualize the potential "blast radius" of a security gap.

 What we expect...

• Academic Background: M.Sc./PhD in Computer Science, Statistics, Engineering, or a related field (or equivalent high-level professional experience).
• Industry Experience: 6+ years in Data Science, with a heavy focus on NLP and solving complex, real-world problems using ML/Deep Learning.
• Technical Mastery: Hands-on experience with PyTorch, Hugging Face, scikit-learn, and SQL. Familiarity with processing large-scale datasets (PySpark, or similar) is highly valued.
• Domain Awareness: Proven ability to apply statistical modeling to cybersecurity, risk management, or complex system analysis. Experience with Vulnerability Management or Graph Theory is a significant plus.
• Product and collaborative Driven Mindset: You are obsessed with understanding the "Why" behind the data. You enjoy learning the nuances of the product and the cybersecurity domain to ensure your DS solutions are highly applicable.

Curiosity & Grit: A passion for diving into "messy" data and finding the signal within the noise of the modern attack surface.