Product Data Scientist, Search Quality Job at Perplexity (Belgrade, London, Berlin)

New

Data Scientist

As part of our Client’s high-performing AI Innovation team, you’ll help design, ...

Location

United States , New York

Salary:

200000.00 - 225000.00 USD / Year

Solomon Page

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)
2+ years of experience as a Data Scientist, Machine Learning Engineer, or applied AI practitioner, with a strong foundation in computer science, algorithms, and software development
Advanced programming skills in Python, with experience building production-grade systems beyond research or experimentation
Solid understanding of machine learning and applied AI concepts, with experience taking solutions from prototype to production
Hands-on experience designing, building, and deploying LLM-driven or GenAI applications, including familiarity with vector databases, embeddings pipelines, or semantic search systems
Practical experience with cloud-based deployments and infrastructure tools (e.g., AWS, Docker, GitHub) and an understanding of modern DevOps practices, containerization, orchestration, caching strategies, and cost-aware design
Strong problem-solving skills and systems thinking, with the ability to balance trade-offs across model quality, scalability, inference latency, cost, and operational complexity
Ability to interpret and implement research ideas and algorithms, actively contributing to research and development initiatives while translating them into production solutions
Excellent communication and collaboration skills, with experience working closely with product managers, engineers, and domain experts to deliver actionable technical solutions
Passion for learning and staying current with the rapidly evolving AI/ML landscape, including emerging best practices for GenAI applications

Job Responsibility

Apply strong problem-solving and critical thinking skills to break down complex, ambiguous requirements into clear, implementable technical components and system designs
Design, build, and maintain AI-powered and data-driven systems with a focus on modern language and multimodal models, including LLM-driven applications, RAG pipelines, and agentic workflows
Evaluate and productionize commercial and open-source LLMs, choosing appropriate models, tools, and techniques for each use case
Develop multi-step agentic workflows that incorporate tools, external data sources, memory, and control logic
Manage the orchestration of production LLM workflows and agentic systems, ensuring reliability and efficiency through prompt routing, state management, retries, fallbacks, and error handling
Design, test, and iteratively refine prompts and system instructions using prompt engineering and tuning techniques to improve model reliability, accuracy, and task performance
Maintain production-grade code and services with automated monitoring and performance tracking, using metrics and alerts to guide continuous improvements in models, prompts, and pipelines
Apply systems thinking to design and optimize AI and LLM systems, balancing quality, scalability, latency, cost, and operational complexity, while implementing efficiency improvements using model selection, prompt design, batching, caching, and retrieval strategies
Define and implement evaluation and observability frameworks for AI systems, including automated testing, task-specific benchmarks, regression testing for prompts, human-in-the-loop validation, and performance monitoring
Build and integrate AI models into backend systems and APIs to support both real-time and batch inference, ensuring solutions are production-ready, scalable, and efficient

Fulltime

Data Scientist II

Are you excited by the opportunity to use machine learning, NLP, and generative ...

Location

United Kingdom , London

Salary:

Not provided

myGwork - LGBTQ+ Business Community

Expiration Date

Until further notice

Requirements

Experience in data science, machine learning, artificial intelligence, NLP, statistics, applied mathematics, computer science, or a related quantitative area
Experience working with frontier LLMs such as OpenAI's GPTs, Anthropic's Claude, and Google's Gemini, including fine-tuning LLMs and/or SLMs
Strong Python skills and a habit of writing clean, maintainable, well-tested code
A solid grasp of machine learning fundamentals, including supervised and unsupervised learning, feature engineering, model evaluation, model selection, and performance measurement
Experience working with structured, semi-structured, or unstructured data, especially large-scale text or content datasets
Familiarity with common data science and machine learning tools such as Pandas, NumPy, SciPy, Scikit-learn, PyTorch, TensorFlow, or Matplotlib
The ability to translate complex and ambiguous requirements into practical, measurable, data-driven solutions, with strong analytical thinking, problem-solving skills, and attention to quality
Clear communication skills, a collaborative approach to working with engineering, product, and business stakeholders, and a genuine interest in building production-ready systems that deliver real user value

Job Responsibility

Design and build machine learning, NLP, and generative AI systems for scientific discovery, knowledge extraction, decision support, and intelligent content understanding
Work with large-scale, complex, and heterogeneous data, including scientific publications, research datasets, knowledge graphs, ontologies, taxonomies, citations, metadata, and content from every scientific discipline
Apply the right technique to each problem, using approaches such as classification, regression, clustering, ranking, feature engineering, deep learning, embeddings, LLMs, retrieval, and generative AI
Develop capabilities for semantic search, information retrieval, entity extraction, content classification, recommendation, ranking, summarization, question answering, and evidence-grounded generation
Build, evaluate, fine-tune, prompt, and integrate models into robust production systems, while continuously improving quality, relevance, reliability, and user value
Write clean, tested, production-quality Python and contribute reusable data science components, packages, and scalable data pipelines for preprocessing, inference, experimentation, monitoring, and continuous improvement
Support deployment, monitoring, model maintenance, drift detection, automated retraining, and ongoing optimization of data science systems
Collaborate with engineering, product, UX, analytics, research, and domain experts, and communicate technical concepts, model behavior, insights, trade-offs, and recommendations clearly to technical and non-technical audiences

What we offer

healthy work/life balance
wellbeing initiatives
shared parental leave
study assistance
sabbaticals
flexible working hours

Fulltime

Sr. Data Scientist

Do you have a relentless passion for data and analytics and a desire to drive fu...

Location

India , Hyderabad

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results). OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results). OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results). OR equivalent experience

Job Responsibility

As an expert in data science, you will take on the most complex business problems and guide the rest of the team in their efforts, helping them formulate approaches to solve challenging problems and discover new opportunities using well-defined algorithms and data sources in the context of customer, engineering, and business needs
You will build everything required to uncover business opportunities and generate actionable insights that move the needle
You will establish causality and conduct experiments to gain insights into quality, health of products, and customer usage
Additionally, you will lead initiatives in search relevance and evaluation, including corpus creation, metric design, and dataset development for diverse modalities, while fine-tuning foundational models to improve intelligent search experiences
You will engage with peers to produce clear, compelling, and data-backed hypotheses and insights which are actionable and influence product and service improvements—crafting the experience millions of customers have with Windows
You will also engage in the peer review process and act on feedback while learning innovative methods, algorithms, and tools to increase the impact and applicability of your results
Through your analysis and research, you will curate and maintain Key Performance Indicators which show trends towards achieving a business goal
You will learn and excel in ways to find patterns in the data that are harder to detect but can lead to achieving our business objectives
Your analysis will not only show us what we're doing right or wrong in our current methodology, but also what customer segments and strategies we should invest more in, and how, for achieving and exceeding our goals

Fulltime

Senior Data Scientist

Our current work includes: Agentic pipelines — multi-step LLM systems with tool ...

Location

United Kingdom , London

Salary:

Not provided

Satalia

Expiration Date

Until further notice

Requirements

5+ years shipping ML models to production — you've dealt with data drift, silent failures, retraining cadences, and the gap between offline metrics and business outcomes
Deep, demonstrable expertise in at least one of: NLP/LLMs, computer vision, recommender systems, or causal inference
Hands-on experience with LLM fine-tuning (LoRA, RLHF, DPO) or building LLM-powered systems (agents, RAG, structured generation)
Strong software engineering habits — version control, testing, code review, CI/CD
Comfort with ambiguity
Clear communication

Job Responsibility

Design and run training pipelines — data curation, model selection, hyperparameter search, ablation studies — and be accountable for model quality on live traffic
Build and maintain production inference services (latency budgets, batching strategies, quantisation, monitoring) that serve WPP's global client base
Architect agentic AI systems: define tool schemas, orchestration logic, evaluation criteria, and failure modes for multi-step LLM workflows
Work across the stack when needed — write the data pipeline, train the model, build the evaluation harness, deploy the service, and debug it when metrics drift
Set technical direction for your workstream: write design docs, make build-vs-buy decisions, and defend your approach with evidence
Mentor and set the quality standards for junior scientists

What we offer

Enhanced pension
Life assurance
Income protection
Private healthcare
Remote working
Truly flexible working hours
Generous Leave - 27 days holiday plus bank holidays and enhanced family leave
Annual bonus
Impactful projects
People oriented culture

Fulltime

Sr Data Scientist

We're Blue River, a team of innovators driven to create intelligent machinery th...

Location

United States , Santa Clara

Salary:

209862.00 - 275000.00 USD / Year

Blue River Technology

Expiration Date

Until further notice

Requirements

Master's degree in Math, Physics, Data Science, or related field plus 5 years of related experience
Implement and deploy computer vision and machine learning-based data pipeline systems using semantic segmentation, image & video classification, object detection, supervised, and unsupervised learning (5 yrs)
Experience working with data engineers, data scientists, software engineers, and field staff through the lifecycle of developing and deploying a machine learning system (4 yrs)
Perform non-parametric statistical tests and analysis on large image-based data sets using sklearn, scikit-image, scipy, and OpenCV (3 yrs)
Write technical documentation, tutorials, and summaries to train data collection teams and conduct on-site training (3 yrs)
Deploy scalable cloud-based solutions to mine, preprocess, resize, crop, rectify, and filter image-based data sets (5 yrs)
Implement code using Python libraries, including NumPy, SciPy, OpenCV, Pandas, Seaborn, Matplotlib, CUDA, Pytorch, and TensorFlow (5 yrs)
Design, implement, debug, and deploy stereo image-based data pipelines using Apache TeamCity, AWS Airflow, Redis, Google appsheet, Data bricks datatables, Celery, and advanced search solutions on LabelBox with open source models such as CLIP and BLIP (6 mos)
Design, build, and debug custom Python pipelines using Python Functools for processing large image datasets, deploy these pipelines using Docker and Docker-compose (1 yr)
Use statistical sampling algorithms to design efficient data collection methods for large stereo camera-based image datasets and coordinate data collection (6 mos)

Job Responsibility

Define, curate, and manage datasets of images, sensor data, and scenarios that are designed to increase the trust and safety of autonomy
Work closely with data engineers and field data capture technicians to mine fleet data and identify open needs
Define frameworks for cataloging and searching scenario-based data to serve multiple stakeholders, including computer vision and robotics teams
Monitor, investigate, and fix data ingestion issues related to dataset curation for training and testing computer vision algorithms
Investigate data quality and actively participate in conceptualizing and developing short and long-term solutions
Provide data and infrastructure support to internal teams
Provide guidance to improve the stability, security, efficiency, and scalability of image data pipelines
Improve code quality through writing unit tests, automation, and performing code reviews
Examine the correlation between customer experience and virtual performance in like scenarios
adjust as needed

What we offer

Eligibility for Blue River's bonus and benefit programs

Fulltime

Senior Data Scientist AI/ML

Data sits at the heart of the company. This role ensures that Awin can fully lev...

Location

Germany; Romania; United Kingdom; Spain; Italy; Germany; France; Poland , Berlin; Iași; London; Madrid; Milano; München; Paris; Warsaw

Salary:

Not provided

Awin Global

Expiration Date

Until further notice

Requirements

Bachelor's degree or higher in Statistics, Mathematics, Data Science, AI/ML, or related field
6+ years of experience in Data Science or AI, with strong exposure to platform-level enablement or ML Ops-aligned environments
Demonstrated expertise in generative AI models and tooling (e.g. standardized evaluation, AI-specific observability, safe rollback mechanisms, retrieval-quality assessment etc)
Experience designing scalable AI architecture components, model pipelines, inference patterns, vector search, feature engineering standards, and monitoring frameworks
Proven experience of creating and maintaining end to end AI tools
Proven ability to mentor teams on AI methodologies, experimentation, and adoption of platform tooling
Collaborative, proactive, and customer-focused approach to enabling product and engineering teams

Job Responsibility

Define, maintain and drive adoption of AI/ML standards, patterns, and reusable components to enable efficient model development across teams
Partner with Data Engineering and Platform Engineering to evolve core AI platform capabilities, ensuring scalability, governance, and robustness
Advise product teams on model design choices, data readiness, evaluation strategies, and responsible AI practices
Develop and implement frameworks, guidelines, and reference architectures to support enterprise-wide adoption of AI and generative AI
Evaluate new AI technologies, tools, and workflows, driving continuous improvement of the platform
Develop and maintain an AI experimentation sandbox that enables teams to prototype and test new models and tooling efficiently
Ensure data quality, feature standardization, and reproducibility across the AI lifecycle
Mentor and coach teams on AI methods, experimentation, and best-practice platform usage
Communicate complex concepts clearly to stakeholders, enabling strategic decision-making and alignment

What we offer

Flexi-Week and Work-Life Balance
Remote Working Allowance
Flexi-Office
Meal Vouchers
Health & Wellbeing (insurance covers several types of health, vision and / or dental treatments for you and for up to one additional family member)
Remote Working Furniture Package (after 3 months of employment)
Appreciation (peer-to-peer voucher program)

Fulltime

Principal Data Scientist - Rentals Shopping

Zillow Group's mission is to give people the power to unlock life's next chapter...

Location

United States , Remote-USA

Salary:

178300.00 - 284700.00 USD / Year

Zillow

Expiration Date

Until further notice

Requirements

Ph.D. or Master's degree in a quantitative field (e.g., Statistics, Economics, Computer Science), or equivalent practical experience
Substantial experience (typically 8+ years) in quantitative analysis, advanced modeling, and experimentation at scale in consumer-facing technology environments
Expert in SQL and Python, with experience applying statistical modeling (e.g., causal inference, time series) in big data environments such as Databricks or Snowflake
Proven track record of shaping long-term product roadmaps and driving meaningful business outcomes through data-driven insights
Ability to influence senior cross-functional leaders and turn complex analysis into clear, executive-ready recommendations and action plans
Comfortable leading in a complex business area with significant autonomy, setting direction and driving execution across partners

Job Responsibility

Drive the long-term data strategy for the Rentals Shopping pillar, using deep analysis of consumer behavior and market dynamics to identify high-impact growth opportunities and inform the product roadmap
Elevate statistical rigor, modeling, and experimentation practices across Rentals to enable high-confidence decision-making
Partner with product, engineering, and design leaders to translate complex analysis into clear, actionable product and business strategies
Lead analytical and modeling work across critical problem spaces such as rental search relevance, ranking, personalization, or marketplace efficiency
Design and guide robust A/B tests and other experimentation frameworks to measure the impact of new features and optimizations in the rental shopping experience
Apply modern AI (including LLMs and agentic workflows) to increase data science velocity, improve model quality, and scale intelligent user-facing solutions across the Rentals marketplace
Coach and mentor data scientists, providing technical leadership and helping to unblock complex analytical and modeling challenges

What we offer

Equity awards based on factors such as experience, performance and location

Fulltime

Principal Data Scientist

Microsoft AI (MAI) builds an integrated consumer AI ecosystem across search, bro...

Location

United States , Redmond

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role

Job Responsibility

Mentor data scientists to drive Microsoft Content product analysis and provide insights
Drive the AI Agents into Data Analysis to improve efficiency and enable data analysis for people with limited data knowledge
Partner closely with Microsoft Content Dev/PM Team and data scientists from other Product (Edge, Copilot, Ads and Search)
Develop Agent for data analysis across Microsoft Content Org
Provide daily analysis, including standardized data collection, analysis, reporting, and interpretation
Validate analytical approaches and results
Apply LLM based AI skills, statistical modeling, data mining, and experimentation to large datasets
Define and deliver metrics that accurately measure user and business
Design and execute experiments across user and demand dimensions
Translate strategy into clear, actionable, and measurable plans, sharing progress and results with stakeholders

Fulltime

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Product Data Scientist, Search Quality

Job Description

Job Responsibility

Requirements

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