Work with HelloFresh in Warsaw and its HelloTech organisation, HelloFresh’s global technology backbone with more than 1000 people, building the digital products that power our end-to-end food experience. From meal kits and ready-to-eat meals to specialty offerings like pet food and premium meat & seafood, HelloTech creates the platforms that bring tailored food solutions to millions of customers every month.

Our subscription-based, direct-to-consumer model relies on technology at every step, from customer-facing apps and personalization logic to pricing, forecasting, supply chain optimization, and initiatives that help reduce food waste. While our brands operate independently to serve distinct customer needs, they are united by shared platforms, data, and operational excellence built by HelloTech.

HelloTech works in autonomous, cross-functional alliances, each owning a specific product or domain end to end. By working with our Warsaw office, you will help shape scalable, data-driven products used across our markets, working with a modern tech stack and international teams to continuously improve how people discover, order, and enjoy HelloFresh’s products, today and in the future.

About the role: What's in the Box

As Senior Data Scientist in the Risk and Fraud Management squad, you will be responsible for building, deploying, and maintaining machine learning models that protect HelloFresh from fraud while enabling business growth through intelligent risk assessment. You will monitor model performance for anomalies and communicate insights with stakeholders to ensure optimal impact. Your work will be crucial to prevent payment and voucher fraud at checkout, and optimize the ship & collect process for recurring customers. Hence you will have a direct impact on the company's revenue protection and customer experience goals.

In this role, you will design and implement classification, regression, and uplift models which take into account various data sources, ranging from payment transactions, customer behavior, to fraud patterns and risk signals. Your models will power both real-time predictions at checkout and offline batch inference for subscription fulfillment decisions. Additionally, you will drive experiments to measure the business impact of your models and continuously improve their performance.

To succeed in this role you will be curious, a fast learner, and someone who relentlessly prioritises problem statements and tailor the solution accordingly. You will be comfortable suggesting multiple solutions based on your experience, and prioritizing tasks based on effort and likely impact. As a senior member of the Data Science team, you will jump into problem solving with others as challenges arise, and collaborate with team members.

What you’ll do: The Recipe

• Work on fraud detection and risk assessment models from data collection to production, collaborating closely with cross-functional teams (engineering, product, finance, operations)
• Build, deploy, and maintain machine learning models for:
• Ship & Collect: Offline batch inference for recurring payment risk assessment and subscription fulfillment decisions
• Voucher Fraud Prevention: Real-time inference at checkout to detect and prevent voucher abuse patterns
• Payment Fraud Prevention: Real-time inference at checkout to detect and block fraudulent payment attempts
• Monitor model performance, detect anomalies, and communicate insights and recommendations to technical and non-technical stakeholders
• Leverage classification, regression, and uplift methodologies to continuously improve fraud prevention and risk assessment solutions
• Proactively utilize Generative AI tools to accelerate development cycles, improve code quality, and drive innovative solutions to complex challenges

What you’ll bring: The Ingredients 

• Bachelors, Masters or PhD in statistics, physics, economics, mathematics, computer science, data science or similar
• 3+ years work experience as a (senior) data scientist, preferably in e-commerce, fintech, or fraud detection
• Strong experience with classification and regression models; familiarity with uplift modeling is a plus
• Fluency in Python (Numpy, Pandas, Scikit-learn, XGBoost, LightGBM) and experience with Spark/PySpark, Databricks
• Experience with AWS services (SageMaker), workflow orchestration (Airflow/Prefect), and feature stores (Tecton is a plus)
• In-depth knowledge of handling imbalanced datasets, optimizing precision/recall trade-offs, and evaluating models in production
• Experience with real-time model inference, A/B testing, and measuring business impact of ML models
• Familiarity with software development practices (Git, Docker, CI/CD pipelines)
• Strong communication and collaboration capabilities with technical and non-technical stakeholders

Above all, we are looking for individuals who will make HelloFresh better. We believe there are many different ways of developing skills and we love diverse experiences! So even if you don’t “tick all the boxes” but think you’d thrive in this role, we would really like to learn more about you.

What we offer: The Toppings

• Global collaboration at scale: Collaborate with experienced engineers and product partners across HelloTech’s international teams, in a culture of active knowledge sharing.
• Technology with real-world impact: Build and operate modern systems at global scale, supporting 6+ millions of customers and complex supply chain operations.
• Technical/Product/Design leadership: Drive best practices and influence architecture/design, quality, and ways of working in an autonomous, product-led setup.
• End-to-end development/delivery: Drive decisions from problem definition to production, improving systems and enabling long-term scalability.
• Access to workspace at Warsaw Centre Point. The hub offers modern facilities including showers, breakout zones, outdoor space, cycle parking, and refreshments (coffee, soft drinks, and fruit).

Are you the missing ingredient? If this sounds like a tasty opportunity, we’d be excited to hear from you. We aim to review your profile and respond within 5 business days.

#Data

Work with HelloFresh in Warsaw and its HelloTech organisation, HelloFresh’s global technology backbone with more than 1000 people, building the digital products that power our end-to-end food experience. From meal kits and ready-to-eat meals to specialty offerings like pet food and premium meat & seafood, HelloTech creates the platforms that bring tailored food solutions to millions of customers every month.

Our subscription-based, direct-to-consumer model relies on technology at every step, from customer-facing apps and personalization logic to pricing, forecasting, supply chain optimization, and initiatives that help reduce food waste. While our brands operate independently to serve distinct customer needs, they are united by shared platforms, data, and operational excellence built by HelloTech.

HelloTech works in autonomous, cross-functional alliances, each owning a specific product or domain end to end. By working with our Warsaw office, you will help shape scalable, data-driven products used across our markets, working with a modern tech stack and international teams to continuously improve how people discover, order, and enjoy HelloFresh’s products, today and in the future.

About the role: What's in the Box

The Conversions Tech area enables meal brands to achieve ambitious growth targets through a seamless and high-performing conversion funnel. As a component of the Growth Alliance, this project drives growth for the HelloFresh group by powering marketing with advanced MarTech capabilities and product innovation. The focus is directed toward (re)acquisition, conversion optimization, and data-driven growth strategies.

In the capacity of a Senior Data Scientist within Conversions, the service provider contributes to shaping the intelligence that drives customized user journeys across conversion funnels. This involves executing complex feature engineering and optimization efforts, contributing to the data foundations and analytical approaches that power the decisioning platform for personalized experiences.

The provided services enable an automated engine that determines the optimal journey for a specific user at the appropriate time, based on intent, channel, and campaign context. This involves operating in a highly cross-functional environment, coordinating closely with Product, Engineering, and Marketing to design, evaluate, and scale personalization across various workstreams. This project carries direct responsibility for advancing the data strategy and improving the user experience for the HelloFresh group across global markets.

What you’ll do: The Recipe

• Build and iterate on machine learning models powering personalization that run in production behind high-traffic, performance-critical conversion pages.
• Execute decisioning models that determine the best next step in the conversion funnel for each user.
• Contribute to system design by coordinating with Engineering to ensure data science solutions integrate cleanly into the overall funnel architecture.
• Coordinate directly with Product and Engineering to shape how ML-driven decisions are embedded into the conversion funnels, including where models decide and how failures are handled.
• Direct experimentation design for decisioning models, defining success metrics, guardrails, and how results are interpreted in high-noise, high-traffic environments.
• Maintain model safety and effectiveness in production by monitoring performance, input data reliability, and latency, and iterating when issues are detected.

What you’ll bring: The Ingredients

• 5+ years of professional experience in data science or a related quantitative field.
• Strong foundation in machine learning concepts relevant to personalization and marketing communications.
• Hands-on experience with techniques such as regression, classification, clustering, recommendation systems, and experimentation.
• Practical experience designing and analyzing A/B tests and controlled experiments.
• Experience working with customer behavior data and segmentation.
• Extensive experience with operating in production environments and collaborating closely with engineers.
• Clear, structured communication skills and a collaborative mindset.

Above all, we are looking for individuals who will make HelloFresh better. We believe there are many different ways of developing skills and we love diverse experiences! So even if you don’t “tick all the boxes” but think you’d thrive in this role, we would really like to learn more about you.

What we offer: The Toppings

• Global collaboration at scale: Collaborate with experienced engineers and product partners across HelloTech’s international teams, in a culture of active knowledge sharing.
• Technology with real-world impact: Build and operate modern systems at global scale, supporting 6+ millions of customers and complex supply chain operations.
• Technical/Product/Design leadership: Drive best practices and influence architecture/design, quality, and ways of working in an autonomous, product-led setup.
• End-to-end development/delivery: Drive decisions from problem definition to production, improving systems and enabling long-term scalability.
• Access to workspace at Warsaw Centre Point. The hub offers modern facilities including showers, breakout zones, outdoor space, cycle parking, and refreshments (coffee, soft drinks, and fruit).

Are you the missing ingredient? If this sounds like a tasty opportunity, we’d be excited to hear from you.  We aim to review your profile and respond within 5 business days.

#Data

Work with HelloFresh in Warsaw and its HelloTech organisation, HelloFresh’s global technology backbone with more than 1000 people, building the digital products that power our end-to-end food experience. From meal kits and ready-to-eat meals to specialty offerings like pet food and premium meat & seafood, HelloTech creates the platforms that bring tailored food solutions to millions of customers every month.

Our subscription-based, direct-to-consumer model relies on technology at every step, from customer-facing apps and personalization logic to pricing, forecasting, supply chain optimization, and initiatives that help reduce food waste. While our brands operate independently to serve distinct customer needs, they are united by shared platforms, data, and operational excellence built by HelloTech.

HelloTech works in autonomous, cross-functional alliances, each owning a specific product or domain end to end. By working with our Warsaw office, you will help shape scalable, data-driven products used across our markets, working with a modern tech stack and international teams to continuously improve how people discover, order, and enjoy HelloFresh’s products, today and in the future.

About the role: What's in the Box

The Conversions Tech area enables meal brands to achieve ambitious growth targets through a seamless and high-performing conversion funnel. As a component of the Growth Alliance, this project drives growth for the HelloFresh group by powering marketing with advanced MarTech capabilities and product innovation. The focus is directed toward (re)acquisition, conversion optimization, and data-driven growth strategies.

In the capacity of a Staff Data Scientist within Conversions, the service provider contributes to shaping the intelligence that drives customized user journeys across conversion funnels. This involves directing complex feature engineering and optimization efforts, designing the data foundations and analytical approaches that power the decisioning platform for personalized experiences.

These services enable an automated engine to determine the optimal journey for a specific user at the appropriate time, based on intent, channel, and campaign context. Execution occurs at a strategic level, influencing how personalization is designed, evaluated, and scaled across various workstreams. This project carries direct accountability for advancing the data strategy and improving the user experience for the HelloFresh group across global markets.

What you’ll do: The Recipe

Decisioning, Modeling & Strategy

• Direct and evolve the data and modeling strategy behind customized journeys and funnel decisioning.

• Direct complex feature engineering initiatives that improve decision quality, robustness, and scalability.

• Design, implement, and evaluate machine learning approaches for large-scale personalization and routing decisions.

• Define standards for model validation, monitoring, and experimentation to ensure long-term reliability and impact.

Technical Coordination & Strategy

• Act as a strategic technical resource for Product, Engineering, and Marketing, shaping how decisioning capabilities are embedded into the conversion funnels and experiences.

• Drive alignment across technical workstreams on how personalization is measured, iterated, and scaled.

• Provide technical frameworks for roadmap and prioritization decisions by framing problems in terms of data, impact, and trade-offs.

• Contribute technical assessments to "build vs. buy" decisions related to data science tooling, platforms, and external solutions.

Platform & Enablement

• Define and evolve shared decisioning frameworks and data products used across Conversions and adjacent domains.

• Ensure analytical solutions are production-ready, observable, and efficient to iterate on.

• Provide high-level technical guidance to other data scientists, setting a high bar for analytical rigor and project impact.

AI & Automation

• Coordinate with engineering teams to bring these capabilities safely into production environments.

• Explore how AI and automation can improve decisioning quality, experimentation velocity, and iteration speed.

What you’ll bring: The Ingredients

• A minimum of 10 years of professional experience with a Master's degree, or a minimum of 5 years of professional experience with a Ph.D. degree, in a quantitative field.
• Demonstrated expertise in data science, with a strong emphasis on personalization and marketing communications.
• Deep understanding of machine learning principles and techniques relevant to send personalization and content creation including regression, classification, recommendation systems, clustering, natural language processing, and multi-armed / contextual bandit algorithms.
• Proven ability to solve complex optimization problems that involve a large number of dimensions and optimization targets.
• Proven ability to design and interpret A/B tests and quasi-experiments with synthetic controls to validate hypotheses related to the personalized communication strategy stream.
• Exceptional communication and collaboration capabilities.
• Experience with customer behavior analysis, segmentation, and identifying high-value actions to drive customer lifetime value.
• Experience in leveraging Generative AI (GenAI) models (e.g., LLMs) for content generation, including prompt engineering, model evaluation, and fine-tuning to create engaging and personalized customer communications.

Above all, we are looking for individuals who will make HelloFresh better. We believe there are many different ways of developing skills and we love diverse experiences! So even if you don’t “tick all the boxes” but think you’d thrive in this role, we would really like to learn more about you.

What we offer: The Toppings

• Global collaboration at scale: Collaborate with experienced engineers and product partners across HelloTech’s international teams, in a culture of active knowledge sharing.
• Technology with real-world impact: Build and operate modern systems at global scale, supporting 6+ millions of customers and complex supply chain operations.
• Technical/Product/Design leadership: Drive best practices and influence architecture/design, quality, and ways of working in an autonomous, product-led setup.
• End-to-end development/delivery: Drive decisions from problem definition to production, improving systems and enabling long-term scalability.
• Access to workspace at Warsaw Centre Point. The hub offers modern facilities including showers, breakout zones, outdoor space, cycle parking, and refreshments (coffee, soft drinks, and fruit).

Are you the missing ingredient? If this sounds like a tasty opportunity, we’d be excited to hear from you.  We aim to review your profile and respond within 5 business days.

#Data

Work with HelloFresh in Warsaw and its HelloTech organisation, HelloFresh’s global technology backbone with more than 1000 people, building the digital products that power our end-to-end food experience. From meal kits and ready-to-eat meals to specialty offerings like pet food and premium meat & seafood, HelloTech creates the platforms that bring tailored food solutions to millions of customers every month.

Our subscription-based, direct-to-consumer model relies on technology at every step, from customer-facing apps and personalization logic to pricing, forecasting, supply chain optimization, and initiatives that help reduce food waste. While our brands operate independently to serve distinct customer needs, they are united by shared platforms, data, and operational excellence built by HelloTech.

HelloTech works in autonomous, cross-functional alliances, each owning a specific product or domain end to end. By working with our Warsaw office, you will help shape scalable, data-driven products used across our markets, working with a modern tech stack and international teams to continuously improve how people discover, order, and enjoy HelloFresh’s products, today and in the future.

About the role: What's in the Box

This service provision involves high-level consultancy for the AI Decisioning function. The objective is to provide technical expertise in optimizing the intelligence that transforms customer engagement strategies. The focus is on complex feature engineering and optimization, developing critical data features, and applying advanced analytical techniques to maximize the performance of the AI decisioning platform. These services provide predictive data and continuous optimization that allows an automated engine to determine the right message, for the right customer, at the right time, on the right channel. There is an opportunity to drive business outcomes through enhanced personalization and predictive analytics, while also providing expertise on how Generative AI can automate and scale content in an iterative process with marketing stakeholders.

What you’ll do: The Recipe

Modeling & Optimization Tasks

• Technical Guidance on Predictive Analysis: Provide expertise in the development and application of machine learning models to solve complex business problems, from churn prediction to large-scale personalization.
• Feature Development & Validation: Develop, prepare, and validate the critical data features that fuel models, ensuring they are robust and predictive.
• Model Performance Standards: Drive improvements in model quality and reliability by implementing industry best practices in validation, monitoring, and A/B testing.

Strategic Collaboration & Impact

• Insight Delivery: Partner with Product and Marketing functions, translating complex findings into actionable insights that guide strategy.
• Analytical Consultation: Proactively collaborate with stakeholders to frame business problems, translate needs into analytical solutions, and provide expertise on the use of Generative AI for content optimization.
• Methodological Perspective: Contribute to the success of the project by establishing analytical best practices and sharing a technical perspective to guide methodologies.

What you’ll bring: The Ingredients

Core Skillset:

• Data Science Background: A strong background in data science or a related quantitative field, with demonstrated success in applying machine learning techniques to solve business problems.
• Core Tech Stack Experience: High proficiency in working with Python (including libraries like pandas and scikit-learn) and SQL. Hands-on experience with core machine learning methodologies (e.g., regression, classification) and experimentation (e.g., A/B testing).
• Proactive Execution: A demonstrated ability to be accountable for deliverables from ideation to impact, with a focus on driving measurable outcomes and identifying potential issues before they become critical.

Preferred Experience:

• Domain & Tool Experience: Previous experience in the MarTech or CRM domains.
• Modern Platform Proficiency: Experience with data platforms like Databricks or the PySpark ecosystem, and general familiarity with cloud platforms (AWS, GCP, or Azure).
• Generative AI Knowledge: Familiarity with or a strong interest in leveraging Generative AI models (e.g., LLMs) for content automation, including prompt engineering.

What we offer: The Toppings

• Global collaboration at scale: Collaborate with experienced engineers and product partners across HelloTech’s international teams, in a culture of active knowledge sharing.
• Technology with real-world impact: Build and operate modern systems at global scale, supporting 6+ millions of customers and complex supply chain operations.
• Technical/Product/Design leadership: Drive best practices and influence architecture/design, quality, and ways of working in an autonomous, product-led setup.
• End-to-end development/delivery: Drive decisions from problem definition to production, improving systems and enabling long-term scalability.
• Access to workspace at Warsaw Centre Point. The hub offers modern facilities including showers, breakout zones, outdoor space, cycle parking, and refreshments (coffee, soft drinks, and fruit).

Are you the missing ingredient? If this sounds like a tasty opportunity, we’d be excited to hear from you.  We aim to review your profile and respond within 5 business days.

#Data

Work with HelloFresh in Warsaw and its HelloTech organisation, HelloFresh’s global technology backbone with more than 1000 people, building the digital products that power our end-to-end food experience. From meal kits and ready-to-eat meals to specialty offerings like pet food and premium meat & seafood, HelloTech creates the platforms that bring tailored food solutions to millions of customers every month.

Our subscription-based, direct-to-consumer model relies on technology at every step, from customer-facing apps and personalization logic to pricing, forecasting, supply chain optimization, and initiatives that help reduce food waste. While our brands operate independently to serve distinct customer needs, they are united by shared platforms, data, and operational excellence built by HelloTech.

HelloTech works in autonomous, cross-functional alliances, each owning a specific product or domain end to end. By working with our Warsaw office, you will help shape scalable, data-driven products used across our markets, working with a modern tech stack and international teams to continuously improve how people discover, order, and enjoy HelloFresh’s products, today and in the future.

About the role: What's in the Box

Are you ready to drive a huge business impact? As a Senior Data Scientist for AdTech Search Optimization, you will be responsible for maximizing the performance of the Search channels. This work will be crucial to increase return on investment for the marketing budget. Hence, the services provided will have a direct impact on the company’s goals to drive and increase marketing efficiency.

In this capacity, the service provider will design and implement statistical and machine learning models which take into account various data sources, from internal conversion data to external ads platform data.

To succeed in this project, the provider will be a curious, fast learner, who relentlessly prioritizes problem statements and tailors solutions accordingly. Success involves suggesting multiple solutions based on professional experience and prioritizing tasks based on effort and likely impact.

What you’ll do: The Recipe

• Collaborate as an integral part of an amazing and fun team consisting of highly skilled data scientists and engineers.
• Collaborate closely within cross-functional teams (engineering, product, marketing) to translate business objectives into concrete, data-driven strategies.
• Take responsibility for the delivery and execution of scientific optimization models and algorithms, from data collection to operationalization, and closely align them with non-technical stakeholders.
• Experiment and explore opportunities to constantly improve and refine technical approaches.
• Leverage statistical analysis and machine learning algorithms in development and production to enhance incrementality measurement solutions.
• Think out of the box to come up with new ways to improve the data products delivered to stakeholders.

What you’ll bring: The Ingredients

• Proven track record of scientific work in your Bachelors, Masters or PhD in statistics, physics, economics, mathematics, data science or similar.
• Long-term (3+ yrs) work experience as a (senior) data scientist, preferably in an e-commerce environment 
• Strong marketing domain knowledge as well as experience with in the Google Search ecosystem and attribution models are a huge plus
• In-depth knowledge how to interpret experiment results, how to handle statistical uncertainties and how to apply statistical models such as regressors and classifiers
• Experience with forecasting algorithms, portfolio optimization approaches, as well as Vector Autoregression
• Fluency and long-term experience in Python, including high familiarity with its scientific stack such as Numpy, Pandas, Scikit-learn, Matplotlib, etc. (experience in Databricks is a plus)
• Ability to retrieve (using SQL), manipulate and analyse large, heterogeneous datasets and build data pipelines
• Familiarity with software development practices and tools (Git, Docker, AWS)
• You love to learn, are a critical thinker and creative problem solver who strives for excellence
• You are a team player who loves to collaborate and work with stakeholders from different backgrounds in an international environment
• Exceptional communication and collaboration capabilities.

What we offer: The Toppings

• Global collaboration at scale: Collaborate with experienced engineers and product partners across HelloTech’s international teams, in a culture of active knowledge sharing.
• Technology with real-world impact: Build and operate modern systems at global scale, supporting 6+ millions of customers and complex supply chain operations.
• Technical/Product/Design leadership: Drive best practices and influence architecture/design, quality, and ways of working in an autonomous, product-led setup.
• End-to-end development/delivery: Drive decisions from problem definition to production, improving systems and enabling long-term scalability.
• Access to workspace at Warsaw Centre Point. The hub offers modern facilities including showers, breakout zones, outdoor space, cycle parking, and refreshments (coffee, soft drinks, and fruit).

Are you the missing ingredient? If this sounds like a tasty opportunity, we’d be excited to hear from you.  We aim to review your profile and respond within 5 business days.

#Data

Salary Range: PLN 350,700 - 474,400 + Benefits + Equity

Subject to alignment to the responsibilities and duties of the role.

About Graphcore

At Graphcore, we’re building the future of AI compute.We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.

Job Summary 
We are seeking a Data Scientist / Data Analyst to transform large-scale infrastructure and hardware-level telemetry into actionable insights, predictive intelligence, and automated decision systems.

Working closely with telemetry platform engineers, you will analyze data across the full stack - from data center infrastructure down to chip-level signals (power, thermals, performance counters, reliability indicators) to detect anomalies, predict failures, and optimize system behaviour. This role complements telemetry engineering by extracting intelligence from observability systems and enabling data-driven control loops.

You will operate at the intersection of data science, distributed systems, and infrastructure observability.

Key Responsibilities

Data Analysis & Modelling

• Analyse large-scale telemetry datasets (metrics, logs, events) across multiple layers: data center (clusters, networking, cooling), system (servers, accelerators), silicon-level (on-chip sensors, performance counters, voltage, thermal, error signals).
• Develop anomaly detection models for infrastructure-level events and hardware/silicon anomalies (e.g., thermal hotspots, voltage instability, error rate drift).
• Build predictive models for fault detection and failure forecasting (e.g., hardware degradation, thermal issues, network anomalies). 
• Apply statistical and machine learning techniques to identify patterns and root causes. 

Automation & Intelligence

• Design automated remediation strategies informed by both system and hardware-level signals.
• Collaborate with engineering teams to integrate models into observability and control systems.
• Enable closed-loop optimization using real-time hardware telemetry streams. 

Data Engineering Collaboration

• Work with telemetry engineers on data ingestion pipelines, ensuring data quality and usability.
• Help define schemas, feature extraction pipelines, and aggregation strategies (e.g., down-sampling, windowing).
• Optimize use of time-series databases and analytics platforms. 

Visualization & Reporting

• Build dashboards and visualizations for operational insights (Grafana, Superset, etc.). 
• Present complex data in clear, actionable formats for engineering and leadership. 
• Define KPIs and health metrics for infrastructure systems. 

Cross-Functional Collaboration

• Partner with platform, hardware, and software teams to understand system behaviour. 
• Support debugging, performance analysis, and benchmarking efforts using telemetry data. 
• Contribute to reference designs and best practices for observability and analytics.

Skills and Experience 

Essential:

• BSc/MSc/PhD in Data Science, Computer Science, Statistics, or related field.
• Strong experience with time-series data analysis and large-scale telemetry datasets.
• Proficiency in Python (NumPy, Pandas, SciPy, ML frameworks).
• Experience with:
  • Anomaly detection techniques (statistical + ML-based)
  • Predictive modeling and forecasting
  • Signal processing techniques (filtering, smoothing, FFT or similar is a plus)
  • Data visualization tools (e.g., Grafana, Tableau, Plotly)
• Familiarity with:
  • Time-series databases (e.g., Prometheus, InfluxDB)
  • Observability stacks and monitoring systems
• Strong understanding of data pipelines and distributed systems.
• Excellent communication skills - ability to translate data insights into engineering actions.

Desirable:

• Experience with data center infrastructure, hardware telemetry and cloud platforms.
• Knowledge of monitoring, observability and management solutions in use by hyperscalers.
• Familiarity with root cause analysis in distributed systems.
• Experience deploying models into production.
• Understanding of system architecture (CPU/GPU/accelerators, networking) .
• Experience with real-time analytics frameworks (Kafka, Flink, Spark).

Benefits

In addition to a competitive salary, annual leave policy, medical and dental health plans, a gym card and employee pension (matched up to 4%). We review our benefits on a yearly basis to ensure we offer a valuable and rewarding benefits programme to our employees.  We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

Sponsorship

Applicants for this position must hold the right to work in the Poland. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications.

Role Description

Responsibilities

• Collaborate closely with product managers, designers, and cross-functional partners (Billing, Financial Data Engineering, etc.) to deliver reliable payments functionality.
• Design, build, test, and maintain backend services and APIs powering financial transactions.
• Work with metrics and logging systems to ensure visibility and observability of the payment infrastructure.
• Acts as a technical lead across projects and teams.
• Sets long-term technical direction and ensures engineering excellence.
• Drives cross-team collaboration and mentors engineers.
• Develops intuitive product instincts and uses data to shape technical and product strategy.

On-call work may be necessary occasionally to help address bugs, outages, or other operational issues, with the goal of maintaining a stable and high-quality experience for our customers.

Requirements

• 9+ years of experience in software engineering or related industry roles.
• Professional experience in backend engineering, preferably with large-scale systems.
• Proficiency in any backend programming language (we’re using Python in Payments, but being language agnostic we know the language is mainly the tool). 
• Solid understanding of distributed systems, transactions, and service reliability.
• Strong communication skills, particularly when working across time zones.

Preferred Qualifications

• Experience with payment systems or financial transaction infrastructure.
• Experience with observability tools (Grafana, Prometheus).
• Passion for fostering technical growth within teams 
• Experience with platforms like Databricks for data engineering and analytics is a plus.

Compensation

Company Overview 

PandaDoc empowers more than 60,000 growing organizations to thrive by taking the work out of document workflow. PandaDoc provides an all-in-one document workflow automation platform that helps fast scaling teams accelerate the ability to create, manage, and sign digital documents including proposals, quotes, contracts, and more. For more information, please visit https://www.pandadoc.com.

What You'll Do

Experimentation & Causal Strategy

• Lead the Experimentation Roadmap: Define, champion, and execute a strategic roadmap for measuring impact across PandaDoc, focusing on high-leverage business questions related to customer workflows, churn risk, and long-term value (LTV).
• Advanced Experiment Design: Design, implement, and rigorously analyze complex A/B tests, multivariate experiments, and adaptive experimentation methods, including the application of Bayesian experimentation, to assess the effectiveness of proposed product changes and business levers.
• Causal Inference Beyond A/B: Apply advanced causal inference techniques (e.g., difference-in-differences, synthetic control, propensity score matching, and instrumental variables) to scenarios where randomized controlled trials (RCTs) are infeasible.
• Deep Dive Analysis: Conduct complex, proactive, and exploratory analysis to discover latent user behavior, emerging trends, and root causes of changes in key metrics, translating these findings into actionable product and business insights.
• Develop Measurement Frameworks: Define, instrument, and govern a unified Key Performance Indicator (KPI) framework that maps low-level product health metrics to high-level business outcomes, ensuring consistent and scalable measurement across the organization.

Technical Leadership & Influence

• Scaling Data Science: Partner with Data Engineering to design and build scalable, self-serve experimentation tooling and reusable analytical assets and frameworks (e.g., causal machine learning models) that empower other analysts and data consumers.
• Strategic Influence: Act as a strategic thinker by translating complex statistical findings into clear, compelling, and actionable business narratives for cross-functional partners and senior leadership (VP/C-suite), driving strategic decisions and investment priorities.
• Mentorship and Training: Serve as a technical subject matter expert, training and mentoring junior and mid-level data scientists on best practices in statistical rigor, experimental design, and causal modeling.

About You

Qualifications

• Experience: 6+ years of professional experience in an applied data science, economics, or product analytics role, with a proven track record of leveraging experimentation and causal inference methods to drive significant business impact.
• Education: B.A. or B.S. in Mathematics, Statistics, Economics, Computer Science, or a related quantitative discipline. A Master’s degree in a quantitative field (e.g., Statistics, Data Science, Econometrics, Operations Research) is preferred, but not required.

Required Technical Expertise

• Causal Inference: Demonstrated expertise in applying a wide range of Causal Inference methods, e.g. Quasi-Experimentation, Matching Methods (PSM), Difference-in-Differences, and/or Instrumental Variables.
• Experimentation Methodologies: Expertise in advanced statistical methodologies for A/B testing, including sample size calculations, sequential testing, dealing with interference/network effects, variance reduction techniques (e.g., CUPED), etc.
• Deep Analytical Methods: Mastery of advanced statistical modeling, time-series analysis, and quantitative methods necessary to perform thorough exploratory data analysis, produce timely insights, and provide actionable recommendations.
• Programming: Advanced proficiency in Python or R for statistical modeling, with experience using relevant data science packages (e.g., SciKit-Learn, numpy, pandas).
• Data Tools: Expert-level proficiency in SQL and experience working with established data warehouses (e.g., Snowflake, Postgres).
• Data Pipelining: Experience with data transformation and workflow management tools such as dbt, Airflow, or Databricks is a strong plus.

Key Attributes

• Strategic Communication & Influence: Possesses exceptional communication, presentation, and data storytelling skills with a consistent record of influencing cross-functional partners and leadership at all levels, particularly in navigating and driving consensus in unstructured or ambiguous environments.
• Change Management: Proven ability to drive organizational change management in environments where experimentation and data-driven decision-making are not yet widely adopted.
• Thrive in ambiguity: Ability to navigate significant ambiguity, translate complex business questions into clear analytical frameworks, and manage multiple competing priorities in a fast-paced environment.
• Relevant Experience: Experience in a SaaS domain and a strong focus on Product Data Science are strongly preferred.

Company Culture 

We're known for our work-life balance, kind co-workers, & creative virtual team-bonding events. And although our Pandas are located across the globe, we stay connected with the help of technology and ensure that everyone on our team feels, well, like a team.

Pandas work best when they're happy. We retain our talent by upholding our values of integrity & transparency, and selling a product that changes the lives of our customers. Our attainment of awards such as Best Workplace, Best StartUp Employer and a Stevie Award for Best Employers demonstrate our commitment to our culture.

Check out LinkedIn to learn more. 

Benefits

• Competitive salary (If you are located in Poland the salary range is 320-350 PLN annually/gross)
• Remote-first approach with the option for hybrid work from our offices in Kyiv, Warsaw, and Lisbon.
• We value long-term collaboration, whether through typical employment contract, employment of record or B2B arrangements. Be aware that contract type and benefits vary by location - feel free to clarify with our recruiters).
• Work schedule aligned with EU time zones.
• Honest, open culture that values constructive feedback.
• Professional and personal development within a collaborative, supportive team.
• Stable yet growing SaaS product offering an agile environment, ownership, start-up energy, and strong technical challenges.

PandaDoc is an Equal Opportunity Employer. We are committed to equal treatment of all employees without regard to race, national origin, religion, gender, age, sexual orientation, veteran status, physical or mental disability or other basis protected by law.

EXTERNAL RECRUITERS
Approval Requirement
The use of external recruiters/staffing agencies requires prior approval from our HR Team. The HR Team at PandaDoc requests that external recruiters/staffing agencies not to contact PandaDoc employees directly in an attempt to present candidates. Complying with this request will be a factor in determining future professional relationships with PandaDoc.

Company Overview 

PandaDoc empowers more than 60,000 growing organizations to thrive by taking the work out of document workflow. PandaDoc provides an all-in-one document workflow automation platform that helps fast scaling teams accelerate the ability to create, manage, and sign digital documents including proposals, quotes, contracts, and more. For more information, please visit https://www.pandadoc.com.

What You'll Do

Experimentation & Causal Strategy

• Lead the Experimentation Roadmap: Define, champion, and execute a strategic roadmap for measuring impact across PandaDoc, focusing on high-leverage business questions related to customer workflows, churn risk, and long-term value (LTV).
• Advanced Experiment Design: Design, implement, and rigorously analyze complex A/B tests, multivariate experiments, and adaptive experimentation methods, including the application of Bayesian experimentation, to assess the effectiveness of proposed product changes and business levers.
• Causal Inference Beyond A/B: Apply advanced causal inference techniques (e.g., difference-in-differences, synthetic control, propensity score matching, and instrumental variables) to scenarios where randomized controlled trials (RCTs) are infeasible.
• Deep Dive Analysis: Conduct complex, proactive, and exploratory analysis to discover latent user behavior, emerging trends, and root causes of changes in key metrics, translating these findings into actionable product and business insights.
• Develop Measurement Frameworks: Define, instrument, and govern a unified Key Performance Indicator (KPI) framework that maps low-level product health metrics to high-level business outcomes, ensuring consistent and scalable measurement across the organization.

Technical Leadership & Influence

• Scaling Data Science: Partner with Data Engineering to design and build scalable, self-serve experimentation tooling and reusable analytical assets and frameworks (e.g., causal machine learning models) that empower other analysts and data consumers.
• Strategic Influence: Act as a strategic thinker by translating complex statistical findings into clear, compelling, and actionable business narratives for cross-functional partners and senior leadership (VP/C-suite), driving strategic decisions and investment priorities.
• Mentorship and Training: Serve as a technical subject matter expert, training and mentoring junior and mid-level data scientists on best practices in statistical rigor, experimental design, and causal modeling.

About You

Qualifications

• Experience: 6+ years of professional experience in an applied data science, economics, or product analytics role, with a proven track record of leveraging experimentation and causal inference methods to drive significant business impact.
• Education: B.A. or B.S. in Mathematics, Statistics, Economics, Computer Science, or a related quantitative discipline. A Master’s degree in a quantitative field (e.g., Statistics, Data Science, Econometrics, Operations Research) is preferred, but not required.

Required Technical Expertise

• Causal Inference: Demonstrated expertise in applying a wide range of Causal Inference methods, e.g. Quasi-Experimentation, Matching Methods (PSM), Difference-in-Differences, and/or Instrumental Variables.
• Experimentation Methodologies: Expertise in advanced statistical methodologies for A/B testing, including sample size calculations, sequential testing, dealing with interference/network effects, variance reduction techniques (e.g., CUPED), etc.
• Deep Analytical Methods: Mastery of advanced statistical modeling, time-series analysis, and quantitative methods necessary to perform thorough exploratory data analysis, produce timely insights, and provide actionable recommendations.
• Programming: Advanced proficiency in Python or R for statistical modeling, with experience using relevant data science packages (e.g., SciKit-Learn, numpy, pandas).
• Data Tools: Expert-level proficiency in SQL and experience working with established data warehouses (e.g., Snowflake, Postgres).
• Data Pipelining: Experience with data transformation and workflow management tools such as dbt, Airflow, or Databricks is a strong plus.

Key Attributes

• Strategic Communication & Influence: Possesses exceptional communication, presentation, and data storytelling skills with a consistent record of influencing cross-functional partners and leadership at all levels, particularly in navigating and driving consensus in unstructured or ambiguous environments.
• Change Management: Proven ability to drive organizational change management in environments where experimentation and data-driven decision-making are not yet widely adopted.
• Thrive in ambiguity: Ability to navigate significant ambiguity, translate complex business questions into clear analytical frameworks, and manage multiple competing priorities in a fast-paced environment.
• Relevant Experience: Experience in a SaaS domain and a strong focus on Product Data Science are strongly preferred.

Company Culture 

We're known for our work-life balance, kind co-workers, & creative virtual team-bonding events. And although our Pandas are located across the globe, we stay connected with the help of technology and ensure that everyone on our team feels, well, like a team.

Pandas work best when they're happy. We retain our talent by upholding our values of integrity & transparency, and selling a product that changes the lives of our customers. Our attainment of awards such as Best Workplace, Best StartUp Employer and a Stevie Award for Best Employers demonstrate our commitment to our culture.

Check out LinkedIn to learn more. 

Benefits

• Competitive salary (If you are located in Poland the salary range is 320-350 PLN annually/gross)
• Remote-first approach with the option for hybrid work from our offices in Kyiv, Warsaw, and Lisbon.
• We value long-term collaboration, whether through typical employment contract, employment of record or B2B arrangements. Be aware that contract type and benefits vary by location - feel free to clarify with our recruiters).
• Work schedule aligned with EU time zones.
• Honest, open culture that values constructive feedback.
• Professional and personal development within a collaborative, supportive team.
• Stable yet growing SaaS product offering an agile environment, ownership, start-up energy, and strong technical challenges.

PandaDoc is an Equal Opportunity Employer. We are committed to equal treatment of all employees without regard to race, national origin, religion, gender, age, sexual orientation, veteran status, physical or mental disability or other basis protected by law.

EXTERNAL RECRUITERS
Approval Requirement
The use of external recruiters/staffing agencies requires prior approval from our HR Team. The HR Team at PandaDoc requests that external recruiters/staffing agencies not to contact PandaDoc employees directly in an attempt to present candidates. Complying with this request will be a factor in determining future professional relationships with PandaDoc.

Work with HelloFresh in Warsaw and its HelloTech organisation, HelloFresh’s global technology backbone with more than 1000 people, building the digital products that power our end-to-end food experience. From meal kits and ready-to-eat meals to specialty offerings like pet food and premium meat & seafood, HelloTech creates the platforms that bring tailored food solutions to millions of customers every month.

Our subscription-based, direct-to-consumer model relies on technology at every step, from customer-facing apps and personalization logic to pricing, forecasting, supply chain optimization, and initiatives that help reduce food waste. While our brands operate independently to serve distinct customer needs, they are united by shared platforms, data, and operational excellence built by HelloTech.

HelloTech works in autonomous, cross-functional alliances, each owning a specific product or domain end to end. By working with our Warsaw office, you will help shape scalable, data-driven products used across our markets, working with a modern tech stack and international teams to continuously improve how people discover, order, and enjoy HelloFresh’s products, today and in the future.

About the role: What's in the Box

This position is for an expert in developing and deploying large-scale recommender systems. The service provider will engage with a high-impact team of data scientists, focusing exclusively on menu personalization. As a Senior Data Scientist, the role involves a pivotal part in designing, implementing, and improving personalized recommendation algorithms for culinary products across global markets.

Expect to have a tangible impact on customer experience and business growth by ensuring customers are presented with the most relevant menu options. This involves working closely with other personalization Data Scientists, as well as Data, Backend, and Machine Learning Engineers, to deliver statistical solutions and ML models to production. Success in this role requires a curious mindset, the ability to prioritize problem statements, and the expertise to suggest multiple solutions based on potential impact. This role does not include people management responsibilities.

At HelloTech, flexibility and cross-functional collaboration are core to how we work. While this role is aligned to a specific Alliance, strong candidates may also be considered for opportunities across different teams or projects.

What you’ll do: The Recipe

• Become an integral part of a high-impact team covering menu personalization.
• Contribute to designing and implementing the next generation of recommender models, from experimentation and data collection to operationalization.
• Shape the future of customer experience by proposing new personalization approaches and evolving statistical and ML models in pace with future company strategies.
• Design and execute A/B tests to measure the impact of new recommendation strategies on key metrics.
• Work with state-of-the-art technologies like AWS (EMR, Glue, S3, etc), Kafka, PySpark, Airflow, Databricks, MLFlow, and Claude (AI).
• Collaborate closely within other functions (data engineering, backend engineering, ML engineering, product) to translate business objectives into concrete strategies.
• Analyze the performance of models to understand customer behavior and implement technical improvements.
• Contribute to a collaborative and knowledge-sharing environment, providing technical guidance and coaching to team members and stakeholders.

What you’ll bring: The Ingredients 

• Proven track record of scientific work (Bachelor's, Master's, or PhD) in computer science, statistics, physics, economics, mathematics, or data science.
• 3+ years of work experience as a data scientist focused on developing and deploying recommender systems or personalized ML models in a production environment.
• In-depth knowledge of various recommendation algorithms, evaluation metrics, and the practical challenges of maintaining a modern recommender system.
• Fluency in Python, including high familiarity with its scientific stack (Numpy, Pandas, Scikit-learn, Matplotlib). Experience in Databricks and PySpark is a plus.
• Technical proficiency in SQL for retrieving, manipulating, and analyzing large datasets.
• Experience with software development practices and tools such as Git, CI/CD, Docker, and AWS.
• Expertise in leveraging Generative AI tools (e.g., Claude, Copilot) to support model development, experimentation, and documentation.
• Exceptional communication capabilities to interact effectively with product managers, UX designers, and business stakeholders.

Above all, we are looking for individuals who will make HelloFresh better. We believe there are many different ways of developing skills and we love diverse experiences! So even if you don’t “tick all the boxes” but think you’d thrive in this role, we would really like to learn more about you.

What we offer: The Toppings

• Global collaboration at scale: Collaborate with experienced engineers and product partners across HelloTech’s international teams, in a culture of active knowledge sharing.
• Technology with real-world impact: Build and operate modern systems at global scale, supporting 6+ millions of customers and complex supply chain operations.
• Technical/Product/Design leadership: Drive best practices and influence architecture/design, quality, and ways of working in an autonomous, product-led setup.
• End-to-end development/delivery: Drive decisions from problem definition to production, improving systems and enabling long-term scalability.
• Access to workspace at Warsaw Centre Point. The hub offers modern facilities including showers, breakout zones, outdoor space, cycle parking, and refreshments (coffee, soft drinks, and fruit).

Are you the missing ingredient? If this sounds like a tasty opportunity, we’d be excited to hear from you.  We aim to review your profile and respond within 5 business days.

#DATA #SCIENCE #AI

The role

Are you passionate about food? Do you consider yourself an expert and enthusiast in developing and deploying large-scale recommender systems? Then this position might be the perfect fit for you!

You will join a high-impact team of data scientists, focusing exclusively on menu personalization. As a Senior Data Scientist, you will play a pivotal role in designing, implementing, and improving our personalized recommendation algorithms for culinary products across HelloFresh’s global markets. In this role, you can expect to have a large and tangible impact on customer experience and business growth by ensuring customers always see the most relevant and appealing menu options. You will work closely with other personalization Data Scientists, as well as Data, Backend, and Machine Learning Engineers, together delivering statistical solutions and ML models to production.

To succeed in this role you should be curious, able to deal with uncertainty, a fast learner, and someone who relentlessly prioritizes problem statements and tailors the solution accordingly. You should also be comfortable suggesting multiple solutions based on your experience, and prioritizing tasks based on effort and potential impact. As a senior member of the team, you will be expected to work independently when necessary, as well as support other team members occasionally. 

What you’ll do

• Join and become an integral part of a high-impact team covering menu personalization.
• Contribute to designing and implementing the next generation of our recommender models, from experimentation and data collection to operationalization and closely aligning them with non-technical stakeholders.
• Shape and transform the future of customer experience at HelloFresh by proposing new personalization approaches and evolving the statistical and ML models in pace with future company strategies.
• Design and execute A/B tests to measure the impact of new recommendation strategies on key metrics.
• Work with state-of-the-art technologies like AWS (EMR, Glue, S3, etc), Kafka, PySpark, Airflow, Databricks, MLFlow, Claude (AI), as well as our in-house MLOPs tools.
• Collaborate closely within other functions (data engineering, backend engineering, ML engineering, product) to translate business objectives into concrete, data-driven personalization strategies.
• Analyze the performance of our models to understand customer behavior, and come up with improvements.
• Contribute to a collaborative and knowledge-sharing environment.

What you’ll bring

• Proven track record of scientific work in your Bachelor's, Master's, or PhD in computer science, statistics, physics, economics, mathematics, data science or similar.
• Long-term (3+ yrs) work experience as a (senior) data scientist focused on developing and deploying recommender systems or personalized ML models in a production environment.
• In-depth knowledge of various recommendation algorithms, evaluation metrics, and the practical challenges of building and maintaining a modern recommender system.
• Fluency and long-term experience in Python, including high familiarity with its scientific stack such as Numpy, Pandas, Scikit-learn, Matplotlib. (Experience in Databricks and PySpark is a plus).
• Ability to retrieve (using SQL), manipulate, and analyse large, heterogeneous datasets.
• Experience with software development practices and tools (Git, CI/CD, Docker, AWS).
• You love to learn, are a critical thinker and creative problem solver who strives for excellence.
• You are a team player who loves to collaborate and work with stakeholders from different backgrounds in an international environment.
• Exceptional communication and collaboration capabilities.
• Experience working with and leveraging Generative AI tools (e.g., Claude, Copilot) to support model development, experimentation, code generation, and documentation.

Interacting with product managers, UX designers, data and backend engineers, as well as business stakeholders, is very much part of our day-to-day, so communication skills are vital. We are looking for strong problem-solvers who can apply their statistical modeling and machine learning skills to a wide range of business problems in the personalization space while also acting as an ambassador to coach team members and stakeholders.

Above all, we are looking for people who will make HelloFresh better. We believe there are many different ways of developing skills, and we love diverse experiences! So even if you don’t “tick all the boxes” but think you’d thrive in this role, we would really like to learn more about you.

Let’s cut to the cheese, this is why you'll love it here

• Box Discount - Amazing discounts on 1 box per week! 75% discount on weekly HelloFresh and Chefs Plate meal kits AND 50% off weekly Factor meal box.
• Health & Wellness - Health & Dental benefits from day 1, a Health Spending Account, unlimited access to the Headspace app to meet your self-care needs, and 25% discount on GoodLife fitness memberships!
• Vacation & PTO - Time off is also an important part of self-care! We offer generous vacation and PTO to help you create a good work-life balance. 
• Family Benefits - A parental leave top-up program for expectant parents.
• Growth & Development - We support your career progression and invest in your continued learning through experiences and initiatives owned by our dedicated L&D team
• Work Hard & Have Fun - From team socials to engaging company days, you’ll have plenty of opportunity to experience the fun!
• Diversity & Inclusion Initiatives - With impactful ERG’s like FreshPride, Women Empowered and LIMES, we are committed to our diversity, equity & inclusion efforts.
• Food Puns - this one is kind of a big dill if you haven’t already noticed. We even have some punny meeting room names!

Flexible Hybrid Approach

At HelloFresh, we know that flexible work arrangements are essential in enabling you to do your best work, while balancing your personal and life needs. Offering remote work flexibility, along with the opportunity to interact and collaborate in the office are all a part of creating a great employee experience. 

To meet these needs, we are pleased to provide Flexible Hybrid work. Flexible Hybrid is a people-first approach that is based on choice, trust, personalization, and empowers teams to choose when and how often they work from the office and work from home, in addition to team days and company days. This means a minimum of 2 days in office per week, with most teams in office between 2-3 days a week.

#LI-HYBRID

HelloFresh Canada uses AI-integrated technology to help us process and evaluate applications more efficiently. This includes tools that screen and assess candidate qualifications based on the requirements for this role. While these tools assist our workflow, all final selection decisions are made by our hiring team.

This is a posting for an existing vacancy. We are actively seeking to fill this position.

#DATA

About Shelf

The enterprise is going agentic — but most AI agents fail when they hit real business complexity. Shelf is changing that.

We’ve built the operating system for agentic AI: a platform that models your policies, workflows, and operational logic into an AI Data Model so agents don’t just respond — they reason. The result? AI that understands how your business actually runs and delivers precise, compliant, auditable outcomes at scale.

Brands like Amazon, Nespresso, HelloFresh, and KeyBank trust Shelf to power AI agents that resolve 85% of cases autonomously, cut handle times by 20–25%, and turn hours-long processes into seconds. We’re partnered with Microsoft, Salesforce, OpenAI, Snowflake, and Databricks — and recognized by Gartner (Cool Vendor) and IDC (Innovator) for our approach.

If you want to sell the infrastructure that makes agentic AI actually work in the enterprise, you’re in the right place.

Our mission is to empower humanity with better answers everywhere.

Summary

The R&D department plays a pivotal role in driving Shelf to disrupt the market. We are looking for Machine Learning experts that are able to deliver end to end with a blend of experience: Python engineering, ML engineering, and pragmatic Data science and Machine learning research. You will ship end-to-end features—from problem framing and experimentation to service deployment, and ongoing operations—quickly and with high quality. Your work will power ML- and LLM-driven services used by top enterprises like Amazon, Mayo Clinic, AmFam, and Nespresso.

This role requires strong Python engineering capabilities coupled with a strong ability to deliver robust ML solutions, along with ML research literacy to choose sound methodologies, define metrics, and evaluate different approaches effectively.

You’ll work in an agile environment, move fast, and own what you ship.

Responsibilities

• Own end-to-end delivery: ideate, research, prototype, productionize, and operate ML-powered services with an expectation to iterate and ship frequently
• Stand up robust training/evaluation pipelines: dataset curation, labeling/feedback loops, experiment tracking, offline/online metrics, and A/B testing
• Solve problems using sound methodology, evaluate approaches along with 
• Transform ML models and LLM workflows (including RAG) into reusable, versioned, observable production services with CI/CD
• Collaborate with Product Owners to shape our product and requirements
• Conduct and receive code reviews; champion engineering excellence, testing discipline, and documentation
• Leverage AI coding assistants to accelerate development and create internal agents that automate parts of the engineering workflow
• Share learnings through demos, docs, and knowledge sessions; contribute to a culture of continuous improvement

Requirements

• 3+ years of professional experience researching and shipping ML-based solutions, with strong Python skills and a track record of delivering fast without sacrificing quality
• Proven experience in owning research problems end-to-end, starting from initial data analysis, through iterative research phases to delivering on production
• Practical NLP/LLM experience: transformers, embeddings, prompt design, and evaluation; ability to choose and justify metrics and methodologies
• Strong backend fundamentals: designing RESTful services, schema design, data modeling, and performance tuning for SQL and NoSQL stores
• Data processing skills: pandas/NumPy; experience with batch/stream processing and ETL orchestration (e.g., Airflow, Step Functions)
• Strong English verbal and written communication

As a plus

• LLM ops and safety: eval frameworks (e.g., RAGAS), guardrails, red-teaming, prompt optimization at scale
• Model optimization: quantization, distillation, pruning; GPU/accelerator-aware serving
• Experience with AWS ML stack (SageMaker, Batch, Step Functions, Lambda, SQS/SNS, DynamoDB, ECS, EC2, S3)
• Vector databases and search: Pinecone, Elasticsearch, pgvector, FAISS, or DeepLake
• Background in reinforcement learning, agent frameworks, or autonomous agents
• Publications, open-source contributions, GitHub portfolio

What Shelf Offers

• B2B contract
• Company Stock Options
• Hardware: MacBook Pro
• Modern technical stack. Develop open-source software
• Premier AI development environment: GitHub Copilot, Claude Code, OpenAI, TypingMind, v0, MCP Servers, plus credits to experiment with emerging AI tools

Why Shelf

• Our Leadership Team has deep knowledge management and AI domain expertise and enterprise SaaS background to execute this plan
• We love our customers and our customers love us. Ask a Shelf customer why, and they’ll tell you it’s because of our innovative capabilities, rock-solid reliability, they truly enjoy working with our people, but most of all – it’s the improvements they see in their business KPIs.
• We have raised over $60 million in funding and our investors include Tiger Global, Insight Partners, Connecticut Innovations, and others
• We have high velocity growth powered by the most innovative product in our category, 3X growth for 3 years in a row
• We now have over 100 employees in multiple U.S. states and European countries, and we have ambitious hiring goals over the next few months

Our Values:

Quality - We’re united by our focus on world‑class Quality. Quality in all things – starting with everything that leaves your desk. Everything you touch – every email, report, campaign, and piece of code – should be outstanding. Your work product should blow people away. Having people look at what you’ve done and say, “Wow.” That’s the standard here. Remember that how you do anything is how you do everything. Focus on craftsmanship—your ability to make things better.

Momentum - for us means that you should know that the things you’re responsible for are moving forward. When you look around and see something that’s stalled, get it moving again. We pride ourselves on “ball movement.” When your boss or team leaves you with something, they should return to see measurable progress. Small, continuous movement is our recipe for success. Constantly look for how to make the work around you move forward. We want you to initiate solutions, ideas, and progress. Don’t wait for it to come to you—reach out and create movement. All the time.

Accountability - We expect every team member to feel that they are accountable for more than anyone might normally expect. Each of us should feel real responsibility for things even at the edge of our control. We consistently share and align on expectations, give each other open and respectful feedback, and use those two drivers to ensure that every agreement we make with one another is clear and complete.

Hard Work - We’re here to do something difficult together. We care intensely about the mission and we expect that from our teammates. That care means that we work hard here. Hard work comes with long hours, extra effort…and real opportunity at Shelf. Your passion for creating and sustaining output is a part of our DNA. Support each other, cheer each other on, drive the mission forward. Great teams sustain intense effort together to win.

Learning Agility - We’re innovating in one of the fastest‑moving spaces in history at a time of accelerating global change. That’s incredibly exciting and requires each of us to commit fully to learning each and every day so that we can be the best at what we do. None of us know everything. All of us can learn anything. Staying open and constantly curious is a key success driver at Shelf. It also requires humility. We prize people who are consistently humble and open to making mistakes and growing from them. Recognize also that learning itself is a skill…we need you to be really good at it. Keep dialing in your own understanding about how you learn best and push yourself to keep growing.

Adapt and Thrive - Overcoming challenges lives deep in our DNA. We have a proud history of understanding and living the reality that obstacles are our opportunities…they’re the key to our success. Change is a constant in our business and fighting change is counterproductive. We need you to be good at being uncomfortable and understand that discomfort is the key to growth. Cultivate your own ability to adapt and know that struggling well is something you’ll share with every team you’re on at Shelf. Our company stories are about thriving through real difficulty…together.

Win Together - We win or lose as a team. Always. Everything you do here is connected to the rest of the organization. Part of our shared team environment demands full honesty…real candor and directness with one another. We expect you to constantly be thinking about how to support your teammates and the company, always acting in service to our shared mission and what’s best for the organization as a whole.

About the role:

We're looking for a Principal Data Scientist to own Readdle's company-wide data science roadmap and drive measurable business impact across the organization.

This is a role for a hands-on technical leader with a business mindset — someone who sets methodological standards, prototypes and productionizes predictive and prescriptive systems, and serves as the internal authority on machine learning, autonomous systems, experimentation, causal inference, optimization, and advanced analytics.

You'll work closely with Product, Engineering, Marketing, Data Platform, and Analytics to embed data-driven decision-making into how we build and grow.

What you will do:

• Own the Data Science roadmap and its technical architecture across the company, ensuring focus on the highest-leverage opportunities and scalable foundations.
• Hands-on build and productionize DS models end-to-end: from hypothesis → prototype → reliable production systems that optimize the proper business metrics.
• Methodological excellence: create, maintain, ensure adoption, and evolve advanced analytics frameworks and enablement cross-functionally, including:
• experimentation design and analysis
• causal inference and incrementality testing (incl. diff-in-diff, synthetic control, uplift, geo experiments, incrementality, etc.)
• measurement frameworks and proxy metric design
• optimization & prescriptive analytics
• Inference in marketing measurement (incl. MMM and Bayesian measurement where applicable)
• Develop predictive and prescriptive capabilities, including revenue & churn prediction, time-series forecasting, anomaly detection, and decision-optimization systems.
• Define and defend proxy measurements when direct measurement is infeasible; select the right method for the task and clearly articulate assumptions/tradeoffs.
• Partner with Data Platform & Analytics teams to jointly ensure high-quality, well-modeled, accessible SSOT data for data science;
• Act as the technical bridge between Product, Engineering, and Marketing to ensure data science is embedded in product lifecycle decisions (discovery, rollout, iteration).
• Own & drive standards around DS reproducibility, testing, CI/CD, version control, packaging, documentation, and monitoring.
• Mentor Senior Data Scientists; create learning paths, review work for methodological rigor, and build a culture of technical excellence.

About you:

• Proven experience as a Principal / Staff Data Scientist (or equivalent) delivering cross-functional, company-level impact and setting technical direction.
• Deep expertise in advanced analytics and measurement, including strong proficiency in:
• experimentation and causal inference
• incrementality measurement, optimization / prescriptive analytics
• defining proxy metrics and causal graphs
• Strong track record of building and productionizing ML systems (predictive and/or prescriptive), including:
• time series forecasting and anomaly detection
• causal graphs / structural thinking (when appropriate)
• MMM and/or marketing measurement approaches (as applicable to the business)
• Deep Python expertise plus at least one library in each category:
• ML/DL: (e.g., scikit-learn, XGBoost/LightGBM, PyTorch, TensorFlow)
• Statistics: (e.g., statsmodels, SciPy, etc.)
• Causal inference: (e.g., DoWhy, EconML, CausalML, causalimpact, PyWhy)
• Strong engineering and MLOps fundamentals, including experience with:
• Python in production, containers, and distributed computing
• CI/CD, testing, version control, reproducibility best practices
• modern data modeling frameworks (e.g., dbt/dataform), orchestration patterns, and model monitoring
• AI developer productivity tools and strong craftsmanship
• Excellent business acumen, stakeholder management, and communication: ability to translate complex methods into clear decisions, assumptions, and tradeoffs for senior leaders.
• Ability to operate across ambiguity, prioritize ruthlessly, and deliver outcomes with high standards of rigor.