Your Role

We're hiring a Senior Data Scientist to join our Athlete Performance team in London. You'll be partnering with world class sports scientists and engineering teams to build algorithms and derive insights from wearable sensors, optical tracking and GPS data that directly impact how athletes train and compete, from local high schools to professional teams.

For this role, we're currently considering candidates who live within a commuting distance of our offices in London or Barcelona. 

As a Senior Data Scientist, you’ll:

• Create and improve algorithms. You'll use your expertise in signal processing to run mathematical and statistical operations on raw sensor and GPS data. Your work will help us derive high-value metrics around human movement classification and physical load quantification, turning raw data into actionable insights for our users.
• Deliver insights at scale. You'll build and deploy models that provide contextualized data to sports scientists, coaches and recruiters.
• Collaborate across teams. You'll work closely with internal product and engineering teams to integrate optical tracking and wearable data, ensuring our products meet the highest standards.
• Lead high-impact projects. You'll own initiatives that meet quarterly goals and help shape the future of athlete performance tracking at Hudl.

Must-Haves

• Strong mathematical background. You're highly skilled in statistical operations and physics-based calculations used to analyze large datasets.
• Proven track record. You've built, maintained and monitored complex AI or ML models in a production environment at scale. You have experience with model observability and managing data drift to ensure long-term performance. You're also comfortable with CI/CD for ML (like MLflow or TFX) and know how to write effective unit tests for stochastic processes. You have a background in biomechanical modeling and signal processing.
• Multi-modal time series expertise. You have demonstrable experience working with multi-modal time series data for deep learning-based analysis and forecasting, and can apply these techniques to derive meaningful insights from complex sensor data streams.
• Product-focused. You understand how to translate raw data into actionable insights that solve real problems for coaches and athletes.

Nice-to-Haves

• Wearable and GPS expertise. You have experience working with wearable devices, IMU sensors, GPS tracking and biometric data.
• Subject matter expertise. You have a deep understanding of biomechanics or exercise physiology and know how to apply these domains to create meaningful performance insights for athletes.
• Knowledge of foundational models. You have experience fine-tuning visual or large language models for new domains.
• Real-time systems experience. You're comfortable working with models designed for low-latency environments.
• Advanced degree. A PhD in biometrics, mathematics or a related field is a plus.

Our Role 

• Champion work-life harmony. We’ll give you the flexibility you need in your work life (e.g., flexible vacation time above any required statutory leave, company-wide holidays and timeout (meeting-free) days, remote work options and more) so you can enjoy your personal life too.
• Guarantee autonomy. We have an open, honest culture and we trust our people from day one. Your team will support you, but you’ll own your work and have the agency to try new ideas.
• Encourage career growth. We’re lifelong learners who encourage professional development. We’ll give you tons of resources and opportunities to keep growing.
• Provide an environment to help you succeed. We've invested in our offices, designing incredible spaces with our employees in mind. But whether you’re at the office or working remotely, we’ll provide you the tech you need to do your best work.
• Support your wellbeing. Depending on location, we offer medical and retirement benefits for employees—but no matter where you’re located, we have resources like our Employee Assistance Program and employee resource groups to support your mental health.

At Superbet, data isn’t a support function, it’s at the heart of every major decision we make. As a Data Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behavior, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Superbet to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers, and Marketers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Superbet moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical/ML methods and bringing them to life in dashboards (we use Tableau).
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engg., Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 2+ years of relevant experience.

What You’ll Do

• Technical AI governance and assurance
• Operationalise AI governance requirements across the full AI lifecycle, from ideation and use-case approval through development, validation, deployment, monitoring, change management, and retirement.
• Review AI and ML systems at a technical level, including model design, feature pipelines, training approaches, validation methods, deployment architecture, monitoring controls, and human oversight mechanisms.
• Translate technical system characteristics into clear governance, risk, and regulatory positions, including mapping to requirements under the EU AI Act, GDPR, LGPD and other relevant frameworks.
• Conduct risk assessments and assurance reviews of AI systems, including risks relating to bias, explainability, privacy, robustness, model drift, misuse, human oversight, transparency, and customer impact.
• Assess whether AI systems have the right documentation, controls, and evidence to support internal governance, regulatory scrutiny, and audit.
• Governance implementation
• Embed governance checkpoints, review criteria, and control requirements into product, engineering, and model development workflows.
• Design and maintain practical governance artefacts such as AI inventories, use-case classification approaches, risk assessment templates, control libraries, testing standards, and review rubrics.
• Define minimum evidence requirements for AI systems, including documentation of intended purpose, system design, data lineage, validation, performance metrics, limitations, human oversight, and post deployment monitoring.
• Audit, compliance, and regulatory readiness
• Perform technical governance reviews and audits of AI systems and supporting processes.
• Test the design and operating effectiveness of AI-related controls and identify remediation actions where gaps exist.
• Produce structured findings, risk opinions, and assurance reports for technical and non-technical stakeholders.
• Support audit and regulatory readiness by building defensible compliance narratives and evidence packs.
• Escalate material issues, control weaknesses, or ethical concerns and track remediation through to closure.
• Monitoring and reporting
• Help define and track meaningful AI governance, risk, and assurance metrics.
• Develop dashboards and reporting views that provide visibility of AI use cases, risk status, control coverage, review outcomes, incidents, and remediation progress.
• Oversee or challenge post-deployment monitoring for model performance, fairness, stability, drift, and adverse customer or business outcomes.
• Business partnership and capability building
• Work directly with data scientists, ML engineers, product teams, and business owners to help them build compliant and trustworthy AI systems without slowing innovation unnecessarily.
• Build organisational capability by translating regulatory and governance expectations into practical guidance, playbooks, and training.
• Keep stakeholders informed on emerging AI regulatory developments, assurance techniques, and good practice.

What We’re Looking For

• Extensive of experience across AI/ML, model risk, technical assurance, or technical AI governance, with a meaningful part of that experience in a regulated environment.
• Preferred prior background as an ML engineer, data scientist, model validator, AI architect, or similar technical role, with subsequent and/or experience in AI governance,
• AI assurance, model risk, or regulatory delivery.
• Experience conducting deep reviews of AI/ML systems beyond policy conformance, including assessment of model design, validation, monitoring, and operational controls.
• Experience translating technical AI concepts into regulatory, risk, audit, or compliance language for senior stakeholders.
• Experience implementing governance processes, controls, and assurance mechanisms in real delivery environments, not just designing high-level frameworks.
• Strong working knowledge of several of the following: EU AI Act, GDPR/LGPD and automated decision-making / profiling considerations, ISO/IEC 42001, ISO/IEC 23894,
• NIST AI RMF, OECD or other leading responsible AI frameworks, sector or market expectations relevant to gambling, customer protection, and technology risk
• Strong understanding of how AI and ML systems are built, evaluated, deployed, and monitored in production.
• Ability to interpret model and system documentation, architecture diagrams, data flows, validation results, and monitoring outputs.
• Familiarity with common ML approaches, LLM / generative AI patterns, model lifecycle tooling, and data/ML platforms.
• Familiarity with cloud-based AI environments such as AWS, Azure, or GCP.
• Stakeholder and delivery skills
• Able to work across technical, product, risk, legal, cybersecurity, and operational teams with credibility.
• Strong written skills, including the ability to produce clear review reports, risk assessments, control evaluations, and executive-ready summaries.
• Comfortable leading workshops, challenging constructively, and driving remediation.
• Able to operate with autonomy and create structure where none exists.
• Strong judgement, pragmatism, and attention to evidence.

The Community You Will Join:

The Homes Supply team is responsible for growing Airbnb’s supply base and ensuring we maintain a diverse, high-quality portfolio of home listings that meet guest expectations for value, variety, and experience. The team also supports hosts globally by enabling efficient planning and execution of growth strategies that align with Airbnb’s mission and resonate with local communities.

The Difference You will Make:

This role is not eligible for relocation support.

As an Acquisition Lead for EMEA, will be entrusted with designing, deploying, and optimizing the host acquisition strategy across EMEA markets. You will lead a growing team of acquisition specialists, coordinate cross-functional efforts, and ensure we hit ambitious growth targets across the region. Your leadership will be critical to scaling our supply footprint and maximizing the impact of every acquisition channel — from FTEs and vendors to paid and organic marketing.

A Typical Day: 

Your day to day activities will be focused on accelerating our acquisition efforts, meeting our goals for New Active Listings on the platform. To reach those objectives, there are several important activities to be performed: 

• Define and own the acquisition strategy for each EMEA market, in close partnership with the Regional Director, Territory Managers and cross-functional partners, ensuring alignment with regional and market-level goals.
• Deploy the strategy across all acquisition channels, ensuring consistent execution across FTE teams, external vendors, paid marketing, and organic acquisition efforts.
• Lead and manage a team of 5–6 FTE acquisition specialists spread across key EMEA countries and markets, setting clear targets, coaching for performance, and maximizing productivity and impact.
• Coordinate acquisition efforts cross-functionally, partnering with Account Management, Marketing, Operations, and other teams to ensure a cohesive approach to supply growth.
• Monitor, review, and analyze acquisition performance across markets and channels, identifying gaps and taking swift corrective actions to keep results on track.
• Report on progress and insights to the Regional EMEA Director, providing data-driven recommendations to refine strategy and resource allocation.

Your Expertise:

• 10+ years of experience in acquisition, business development, sales, or growth roles, ideally within a tech, marketplace, or platform business.
• Proven track record of designing and executing multi-market acquisition or growth strategies across diverse geographies, with a strong preference for EMEA experience.
• 5+ years of people management experience, including leading distributed or remote teams across multiple countries and cultures.

Core Skills

• Commercial acumen — Deep understanding of commercial levers, market dynamics, and how to build and scale acquisition engines that deliver measurable business results.
• Negotiation skills — Strong ability to negotiate with internal and external stakeholders, including vendors, partners, and cross-functional leaders, to drive alignment and outcomes.
• Team & performance management — Demonstrated ability to build, inspire, and manage high-performing teams; skilled at setting goals, coaching talent, and holding teams accountable to deliver results.
• Analytical mindset — Comfortable working with data and analytics tools to assess performance, identify trends, and make data-driven decisions. You don't need to be a data scientist, but you should be able to interrogate data, build dashboards, and translate insights into action.
• Cross-functional coordination — Experience working across multiple teams and stakeholders (e.g., marketing, account management, vendors) to align efforts and maximize impact.
• Strategic thinking — Ability to see the big picture, prioritize effectively, and translate regional goals into actionable market-level plans.

Desirable Skills

• Experience working with external vendors or outsourced teams in an acquisition or sales context.
• Familiarity with paid marketing and organic growth channels as part of a broader acquisition mix.
• Experience in the travel, hospitality, or marketplace industry.
• Multilingual capabilities are a plus given the EMEA scope.

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

Scopely is looking for a Senior Data Scientist to join our Monopoly GO! game team in our Barcelona hub on a hybrid basis, or remotely in Spain or Portugal.

At Scopely, we care deeply about what we do and want to inspire play, every day. We are a global team of game lovers who are developing, publishing, and innovating the mobile games industry, connecting millions of people around the world daily.

What You Will Do 

As a Senior Data Scientist, you will play a key role in supporting game growth by leveraging data to build innovative, player-centric solutions. You won't just analyze data; you will own the lifecycle of data products — from identifying a player pain point to deploying a production-level solution.

• Product Vision & Strategy: Partner with Product Managers and Stakeholders to identify high-value opportunities, helping to define the data science roadmap for the one of the world’s biggest mobile games.
• End-to-End Ownership: Own the process of creating new data products, from initial inception and requirement gathering to technical design, productionalization, and monitoring.
• Player Insights: Analyze player behavior to understand how features impact the game economy, progression, social dynamics, and sentiment.
• Advanced Modeling: Design and implement A/B tests, forecasting, clustering, and ML models that don't just "predict," but provide actionable "decision intelligence."
• Technical Excellence: Provide technical expertise throughout the product life cycle, ensuring high quality, scalability, and efficiency in our Data & Insights team.
• Collaborative Delivery: Work across departments (Product Analytics, Engineering, LiveOps, Marketing) to ensure data solutions are integrated and driving real-world impact for our players.

What We’re Looking For

We want a creative, highly motivated individual who enjoys tackling ambiguous problems and "figuring it out" with practical, scalable solutions.

• Product Mindset: Outstanding problem-solving skills with a "user-first" mentality. You can conceptualize player behavior and determine the best metrics to measure success, even when data is messy or non-existent.
• Technical Stack: Advanced proficiency in Python and SQL. Experience with BI tools (Looker) and visualization libraries (Plotly, etc.).
• Data Engineering Savvy: Experience with data transformation at scale using dbt and Airflow.
• Production Experience: Proven track record of deploying data products to production (on GCS, AWS, or Azure) and implementing monitoring/alerting to ensure service quality.
• Scientific Rigor: Strong background in statistics, A/B testing methodology, and applying ML/AI to improve business understanding.
• Communication: Ability to translate complex methodologies into clear "so-whats" for non-technical stakeholders and business users.

Bonus Points

• Gaming Passion: A deep love for F2P mobile games and an understanding of game loops/economies.
• Specialized Knowledge: Familiarity with causal inference, Bayesian statistics, or MLOps platforms.
• Deep Learning & GenAI: Hands-on experience with LLMs, predictions using Transformers, or other Deep Learning architectures applied to behavioral data or content generation.

Datavant is looking for an enthusiastic and meticulous Data Scientist (Privacy) to join our growing team, which interrogates and assesses client information in terms of the re-identification risk to patients.

As part of the Privacy Science team within Privacy Solutions you will play a crucial role in ensuring that privacy of patients is safeguarded in the modern world of data sharing. As well as working on real data, you will be involved in exciting research to keep us as industry leaders in this area, and stimulating discussions on re-identification risk. You will be supported in developing/consolidating data analysis and coding skills to become proficient in the analysis of large health-related datasets. 

You Will:

• Critically analyse large health datasets using standard and bespoke software libraries
• Discuss your findings and progress with internal and external stakeholders
• Produce high quality reports which summarise your findings
• Contribute to research activities as we explore novel and established sources of re-identification risk

What You Will Bring to the Table: 

• MSc or PhD in Statistics, Mathematics, Physics, Chemistry or similar.
• Familiarity or proficiency with programmable data analysis software R or Python, and the desire to develop expertise in its language
• A good understanding of statistical probability distributions, bias, error and power as well as sampling and resampling methods
• Seeks to understand real-world data in context rather than consider it in abstraction
• Application of scientific methods to practical problems through experimental design, exploratory data analysis and hypothesis testing to reach robust conclusions
• Strong time management skills and demonstrable experience of prioritising work to meet tight deadlines
• Excellent communication skills. Meticulous attention to detail in the production of comprehensive, well-presented reports
• Initiative and ability to independently explore and research novel topics and concepts as they arise, to expand Privacy Solution’ knowledge base
• An appreciation of the need for effective methods in data privacy and security, and an awareness of the relevant legislation
• Familiarity with Amazon Web Services cloud-based storage and computing facilities
• Bonus: Experience with SQL
• Bonus: Experience of creating documents using LATEX
• Bonus: Detailed knowledge of one or more types of health information such as genomics
• Bonus: Experience with public sector work

Perks of joining Datavant in Barcelona

• 25 vacation days
• Daily in-office lunch stipend (and a fully stocked kitchen)  
• Hybrid work model: 2 days/ week in our office in Gracia
• Commitment to professional development opportunities 
• Employee-led initiatives including annual company-wide innovation day & DEI resource groups 
• Comprehensive private health coverage w/ out-of-network reimbursements options 
• Flexible remuneration with Cobee (Restaurant, Transportation, Nursery)
• Peer & company recognition programs
• Monthly educational lunch & learns

Senior Data Scientist — Verify V2 Data Products, Insights & Monetization

Mission

Build the quantitative foundation that proves and amplifies Verify v2's value—transforming verification telemetry into a reliable, customer-facing data infrastructure that demonstrates measurable ROI, optimizes channel economics, and lays the groundwork for an autonomous identity and verification platform.

You'll own the end-to-end data pipeline from raw events to customer-visible metrics that answer the question every customer asks: "What is this product actually worth to my business?"

What You'll Own

1. Customer Value Infrastructure (Prove ROI at Every Level)

Build the metrics that quantify customer-specific business impact:

• Design and maintain a real-time Customer ROI Engine calculating cost-per-successful-verification, fraud savings, conversion lift, and time-to-value by customer, segment, and use case
• Create customer-facing Value Dashboards showing verification success rates vs. industry benchmarks, cost efficiency trends, and projected savings
• Develop attribution models connecting verification outcomes to downstream business metrics (account activations, transaction completion, fraud prevented)

Establish pricing intelligence at the customer level:

• Build granular unit economics visibility: cost-to-serve, margin contribution, and channel mix efficiency per customer
• Model willingness-to-pay signals and usage patterns to inform tiered pricing and custom packaging
• Quantify the revenue impact of workflow configurations (Silent Auth-first vs. SMS fallback economics)

2. Channel Performance & Optimization (Make Every Verification Smarter)

Create a single source of truth for channel economics:

• Unified performance metrics across SMS, Voice, Email, WhatsApp, and Silent Authentication: deliverability, latency, conversion rate, cost-per-success, and failure taxonomy
• Country × carrier × channel performance matrices with confidence intervals and anomaly flags
• Real-time channel health monitoring with automated alerting for degradation

Build the intelligence layer for workflow optimization:

• Predictive models for optimal channel routing (next-best-channel given geography, time, customer segment, historical performance)
• Fallback effectiveness analysis: quantify conversion recovery and cost trade-offs for each fallback path
• Silent Authentication signal analysis: success/rejection drivers, speed benchmarks, and UX impact measurement

3. Product Data Platform (Foundation for Autonomy)

Design data architecture that enables autonomous decision-making:

• Define the canonical event schema and taxonomy for all verification touchpoints (API calls, webhook events, workflow steps, outcomes)
• Build certified, versioned datasets powering self-serve analytics, ML models, and customer-facing products
• Implement data quality infrastructure: lineage tracking, anomaly detection, freshness SLAs, and automated reconciliation

Ship ML/analytics products that move toward autonomous verification:

• Conversion propensity models: predict verification success probability in real-time to optimize routing
• Fraud & abuse detection: anomaly scoring for traffic pumping, IRSF patterns, and bot behavior—with automated response recommendations
• Time-to-verify prediction: forecast completion time to enable SLA commitments and dynamic timeout tuning
• Customer segmentation: behavioral and commercial clustering for personalized workflows and pricing

4. Monetization (Turn Data into Revenue)

Develop data products that customers will pay for:

• Verification Intelligence Suite: premium analytics, industry benchmarks, and deliverability diagnostics
• Workflow Optimizer: ML-driven recommendations for channel sequencing, timeout configuration, and fallback strategies by geography and vertical
• Fraud Protection Package: risk scoring, pumping detection, and abuse pattern alerts with quantified savings

Define commercial success:

• Package entitlements, usage thresholds, and upgrade triggers
• Track attach rates, retention lift, and expansion revenue attributable to data products
• Build the business case for each offering with clear ROI narratives

Key Responsibilities

• Own the customer value narrative: Build and maintain the infrastructure that lets every customer (and our sales team) articulate Verify's ROI in dollars and percentages
• Ship production ML systems: From feature engineering through deployment, monitoring, and iteration
• Create reliable, self-serve data products: Dashboards, APIs, and datasets that scale without manual intervention
• Drive pricing and packaging decisions: Provide the quantitative foundation for how we charge and what we bundle
• Partner across the organization: Work with Product, Engineering, Finance, Sales, and Customer Success to embed data into every decision
• Report to leadership: Own KPI narratives on margin drivers, growth levers, and competitive positioning

Success Measures

What "Great" Looks Like

Core Data Science

• Experimentation design and causal inference (A/B testing, CUPED, uplift modeling, instrumental variables)
• Predictive modeling: classification, survival analysis, time series, real-time scoring
• Anomaly detection with adversarial thinking (fraud patterns, traffic manipulation, abuse signals)
• Customer analytics: segmentation, LTV modeling, churn prediction, cohort economics

Data Engineering Fluency

• Strong SQL; Python (pandas, scikit-learn, PySpark); comfortable shipping production code
• Event-driven architecture: streaming pipelines and real-time analysis and adaptation (Apache Flink), webhook processing, idempotency, late-arrival handling
• Data modeling: star schemas, semantic layers, data contracts, metric certification
• MLOps: feature stores, model monitoring, CI/CD for analytics, orchestration (Airflow/Dagster)

Product & Commercial Analytics

• Pricing analytics: unit economics, willingness-to-pay estimation, margin optimization
• Funnel analysis for multi-step, multi-channel workflows
• Dashboard design and narrative clarity (Looker, Tableau, dbt metrics layer)
• Packaging and monetization strategy for data products

Domain Expertise (Highly Valued)

• CPaaS, verification, or 2FA: OTP mechanics, deliverability constraints, carrier relationships
• Silent Authentication: network-based verification, success/rejection drivers, integration patterns
• Fraud and risk: traffic pumping, IRSF, bot detection, abuse economics
• Privacy and compliance: GDPR/CCPA, data minimization, audit requirements, customer-facing data controls

Background

• 5–8+ years in data science/analytics, with ≥2 years building and shipping data products
• Track record of translating ambiguous business questions into measurable outcomes
• Experience in B2B SaaS, identity/auth, fintech, messaging/telecom, or fraud analytics preferred
• Demonstrated ability to influence product and pricing decisions with data

Why This Role Matters

Verification is shifting from a cost center to a strategic differentiator. The data infrastructure you build will:

1. Prove value — Give every customer undeniable evidence of ROI
2. Optimize economics — Make every verification faster, cheaper, and more reliable
3. Enable autonomy — Lay the foundation for a platform that routes, optimizes, and protects without human intervention

You'll shape how Vonage—and our customers—think about identity verification as a measurable, optimizable, intelligent system.

#LI-WW1

Shift Technology : 

Shift is the leading AI platform for insurance. Shift combines generative, agentic, and predictive AI to transform underwriting, claims, and fraud and risk - driving operational efficiency, exceptional customer experiences and measurable business impact. Trusted by the world's leading insurers, Shift delivers AI when and where it matters most, at scale and with proven results.

The Data Science Team🤖: 

The Data Science team works on a broad range of subjects. We actively participate in the definition and development of our suite of products on fraud detection, anti-money laundering and claim automation.  We have a lot of technical and professional experience in data science, data engineering, coding, business understanding and client interactions. Additionally, we also work on various data types such as structured data, free text, documents and images.

Your key responsibilities will include🧑‍💻:

• Setting up and deploying data processing pipelines, such as data reception (batch or real-time), data cleaning, information extraction, and calibration of fraud detection models.
• Collaborating with clients to understand their needs and incorporating their feedback to enhance our solutions.
• Conducting R&D to drive product innovation (machine learning, NLP, image analysis, trend analysis, chatbots, etc.).
• Supporting the sales team by participating in prospect demos.
• Partnering in an entire Data Science product lifecycle : Understand how sales, legal, product, engineering are connected together to deliver an AI product to clients.

Your profile and requirements✅: 

• You are currently enrolled as a master's degree student in either Mathematics,  Statistics, Computer Science, Machine learning and/or Big Data.
• You must be able to provide an internship agreement (convenio de prácticas) signed by your school or university for 6 months and you are able to start your internship around August 31th in Madrid. 
• You have experience in object-oriented programming (OOP) such as prior internship, school and/or personal projects so you can write quality production code. An experience using C# is a plus.
• You are comfortable dealing with clients.
• Spanish is mandatory at a fluent level and you can communicate clearly in English. French is not mandatory. 

Why join Shift Technology as a Data Scientist Intern ? 

🤸‍♀️Flexibility, autonomy  and adaptability are part of our core values : We are a horizontal organization without bureaucracy (40% of staff are data scientists) but optimal and reduced line management, focus on delivery and development while having a hybrid model.

🧠Learn from inside an AI leader tech company : Join the 13th French Licorne providing hands on training, workshop and sessions with highly experienced AI research Team.  

💶Your commitment, our investment : 1800€ gross monthly gratification, high  conversion rate to full time employee, dedicated HR partner, regular reviews and feedback sessions with your team.

🌍Be part of an international and diverse tech firm : Full english speaking environment with 55 different nationalities across the world and 11 offices locations (Paris, Singapore, Tokyo, Sao Paulo, Mexico City, Boston, Madrid, London, Toronto, Berlin...)

🤝Dealing with big clients and developing business skills & knowledge : Real life experience with Insurance business challenges inside the world of AI.  

What is next ? 🎯

If your application and experience meet our requirements, you can expect :

• Talent Acquisition interview (30 min)
• Technical interview 1 (60 min) 
  Technical interview 2 (60 min) 
• Hiring manager interview (60 min)

The interview process can take 2 to 3 weeks, depending on the interviewer's availability. Be sure that we are doing our best to get back to you with an answer as fast as possible. If you are not getting an update on your application after 10 days, please reach out to our email address. 

The Role

At Super technologies, data isn’t a support function, it’s at the heart of every major decision we make. As a Senior Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behaviour, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Superbet to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers, and Marketers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Superbet moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical/ML methods and bringing them to life in dashboards (we use Tableau).
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and/or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engg., Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 2+ years of relevant experience.

Why Join Us?

• High Impact
  • Your datasets will be used daily by teams making product decisions, running experiments, and driving performance.
• Real Scale, Real Problems
  • Handle serious data volumes. We’re talking millions of events per day, multiple sources, and zero fluff.
• Freedom to Shape
  • Influence our data architecture, tooling, and best practices. You're not just implementing—you’re building.
• Solid Benefits
  • Competitive compensation & performance-based bonuses
  • Open vacation policy & hybrid work flexibility
  • Health support, wellness perks & team social budget

The Role

At Super technologies, data isn’t a support function, it’s at the heart of every major decision we make. As a Senior Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behaviour, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Superbet to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers, and Marketers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Superbet moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical/ML methods and bringing them to life in dashboards (we use Tableau).
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and/or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engg., Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 2+ years of relevant experience.

Why Join Us?

• High Impact
  • Your datasets will be used daily by teams making product decisions, running experiments, and driving performance.
• Real Scale, Real Problems
  • Handle serious data volumes. We’re talking millions of events per day, multiple sources, and zero fluff.
• Freedom to Shape
  • Influence our data architecture, tooling, and best practices. You're not just implementing—you’re building.
• Solid Benefits
  • Competitive compensation & performance-based bonuses
  • Open vacation policy & hybrid work flexibility
  • Health support, wellness perks & team social budget

The Role

At Super technologies, data isn’t a support function, it’s at the heart of every major decision we make. As a Senior Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behaviour, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Superbet to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers, and Marketers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Superbet moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical/ML methods and bringing them to life in dashboards (we use Tableau).
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and/or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engg., Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 2+ years of relevant experience.

Why Join Us?

• High Impact
  • Your datasets will be used daily by teams making product decisions, running experiments, and driving performance.
• Real Scale, Real Problems
  • Handle serious data volumes. We’re talking millions of events per day, multiple sources, and zero fluff.
• Freedom to Shape
  • Influence our data architecture, tooling, and best practices. You're not just implementing—you’re building.
• Solid Benefits
  • Competitive compensation & performance-based bonuses
  • Open vacation policy & hybrid work flexibility
  • Health support, wellness perks & team social budget

The Role

At Super technologies, data isn’t a support function, it’s at the heart of every major decision we make. As a Senior Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behaviour, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Superbet to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers, and Marketers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Superbet moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical/ML methods and bringing them to life in dashboards (we use Tableau).
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and/or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engg., Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 2+ years of relevant experience.

Why Join Us?

• High Impact
  • Your datasets will be used daily by teams making product decisions, running experiments, and driving performance.
• Real Scale, Real Problems
  • Handle serious data volumes. We’re talking millions of events per day, multiple sources, and zero fluff.
• Freedom to Shape
  • Influence our data architecture, tooling, and best practices. You're not just implementing—you’re building.
• Solid Benefits
  • Competitive compensation & performance-based bonuses
  • Open vacation policy & hybrid work flexibility
  • Health support, wellness perks & team social budget

We are looking for an experienced Lead Data Scientist to add to our Data Science team.

Responsibilities:

• Drive the team’s data science vision and ensure alignment with business goals, focusing on ad-tech and revenue optimization.
• Guide and support the growth of data scientists, fostering a collaborative and innovative environment.
• Oversee the development of scalable, high-impact models for ad targeting, bid strategy, and performance analysis.
• Ensure the efficiency and relevance of data pipelines and models, adapting to the dynamic tech landscape.

Technology Stack:

• Proficiency in Python and SQL.
• Experience with manipulation frameworks such as PySpark and Pandas.
• Skilled at using cloud services such as AWS, etc.
• Hands-on experience in DNN models training libraries and frameworks (PyTorch, Hydra, comet etc.)

Qualifications:

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field.
• 5+ years of experience in data science, preferably in a product-focused environment.
• 2+ years experience in AdTech.
• 2+ years experience in a leading role.
• Strong analytical skills with the ability to derive insights from complex datasets.
• Proficiency in statistical modeling and machine learning techniques.
• Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment.
• Based in Barcelona, Spain or ready for relocation.

Why Join Us:

• Opportunity to work on cutting-edge projects with a global impact in the mobile app industry.
• A collaborative and inclusive work culture that values innovation and continuous learning.
• Competitive salary, flexible work arrangements, and comprehensive benefits package.
• Professional development opportunities and career growth prospects within a fast-growing company.

Who we are

Moniepoint is a global fintech building modern financial services for millions of people and businesses across high-growth markets. We provide payments, banking, credit, and financial management tools - reliable products that people and businesses use every day to run their lives, grow their companies, and move money safely.

Our mission is simple: to enable financial happiness for every African, everywhere. And this is day one. We’ve grown rapidly in Nigeria and the UK, and we’re now expanding our product, engineering, and analytics teams. Our work ranges from building financial infrastructure to designing intuitive customer experiences for emerging markets - solving real, meaningful problems at scale.

We onboard over a million new customers each month, process 100s of billions of dollars in payments annually, and support tens of millions of users across our ecosystem. Our teams operate in a fast-paced, high-impact environment alongside international leaders from companies like Glovo, Bolt, Monzo, Klarna, Checkout.com, and Tide. If you want to build our data science function from the ground up, work with one of Africa’s highest-scale fintech data sets, and ship products that influence tens of millions of users, this is an exceptional time to join.

About the role: 

At Moniepoint, data is at the core of everything we do. We are a customer-centric company, and your work will enable our teams to make informed, data-driven decisions that directly impact the success of our business. We are seeking a data-driven, impact-oriented Senior Data Scientist to power Moniepoint’s consumer lending decisions at scale. You will build the models, experiments, and insights that shape how we acquire, underwrite, and retain millions of customers across Nigeria and Africa.

This role is pivotal in driving our pricing, credit limit modelling, and credit model deployment strategy in a growing business with unparalleled opportunities to give access to millions of customers. You’ll collaborate with our amazing Consumer Credit team and drive how we think about risk ranking, product offering, and data infrastructure to create the best personalised offers for our customers. You’ll be responsible for building our first suite of credit risk models and help drive a culture of how we should think about machine learning vs more traditional methods - bringing fresh thinking to inspire both the team and our customers.

Sitting at the intersection of data science, credit risk, and product, you’ll translate complex data into actionable decisions that drive growth with healthy portfolio performance.

Curious about what makes Moniepoint an incredible place to work? Check out posts on how we cultivate a culture of innovation, teamwork, and growth.

What You’ll Do

• Develop and deploy credit scoring, affordability, and behavioural models to support underwriting, pricing, and collections
• Design and run experiments to optimise approval rates, loss rates, and profitability
• Partner with product squads to embed decision logic into real-time systems
• Ensure data quality, compliance, and ethical use of models across all decisioning processes
• Mentor product squads on best practices in experimentation and data-driven decision making
• Provide models to optimise outcomes in collections, churn management and user retention

We would love to hear from you if…

• You’re comfortable with Statistics - and have a Degree or qualifications  in a quantitative field (Statistics, Mathematics, Engineering or similar)
• You have +5 years of experience in data science, decision science, or risk analytics within financial services
• Working knowledge of credit risk, consumer lending, and regulatory considerations
• Proficiency in SQL and at least one modelling/programming language (Python, R)
• Experience with A/B testing, machine learning, collections modelling and churn management
• Ability to translate complex analyses into clear recommendations for business stakeholders
• High ownership mindset and comfort working in fast-paced, cross-functional teams

What we can offer you

• Culture: We put our people first and prioritize the well-being of every team member. We’ve built a company where all opinions carry weight and where all voices are heard. We value and respect each other and always look out for one another. Above all, we are human.
• Learning: We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks.
• Compensation: You’ll receive an attractive salary, pension, health insurance, monthly bonuses, plus other benefits

What to expect in the hiring process

• A preliminary phone call with the recruiter
• A coding exercise on HackerRank - covering core data science theory (math, statistics, linear algebra) and Python fundamentals (data structures & algorithms).
• A take-home assignment
• A technical interview with a Lead in our Data Science Team to review your take-home assignment in depth
• A behavioural and technical interview with the hiring manager

Moniepoint is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates.

Who we are

Moniepoint is a global fintech building modern financial services for millions of people and businesses across high-growth markets. We provide payments, banking, credit, and financial management tools - reliable products that people and businesses use every day to run their lives, grow their companies, and move money safely.

Our mission is simple: to enable financial happiness for every African, everywhere. And this is day one. We’ve grown rapidly in Nigeria and the UK, and we’re now expanding our product, engineering, and analytics teams. Our work ranges from building financial infrastructure to designing intuitive customer experiences for emerging markets - solving real, meaningful problems at scale.

We onboard over a million new customers each month, process 100s of billions of dollars in payments annually, and support tens of millions of users across our ecosystem. Our teams operate in a fast-paced, high-impact environment alongside international leaders from companies like Glovo, Bolt, Monzo, Klarna, Checkout.com, and Tide. If you want to build our data science function from the ground up, work with one of Africa’s highest-scale fintech data sets, and ship products that influence tens of millions of users, this is an exceptional time to join.

About the role: 

We’re looking for a hands-on Senior Data Scientist (Fraud) to help detect, prevent, and reduce fraud across one of the largest financial transaction ecosystems in Africa. Operating at the heart of real-time payments, identity, behavioural risk, and transaction monitoring, this role works at massive scale with direct, real-world impact.

You’ll partner closely with Fraud, Risk, Product, and Engineering teams to design, build, and deploy production fraud models that sit directly in decision flows. Sitting at the intersection of data science, fraud strategy, and product, you’ll translate complex behavioural signals into high-confidence, real-time decisions - balancing fraud loss, customer experience, and regulatory expectations to protect millions of customers and businesses.

Curious about what makes Moniepoint an incredible place to work? Check out posts on how we cultivate a culture of innovation, teamwork, and growth.

What You’ll Do

• Develop and deploy fraud detection, transaction monitoring, and behavioural risk models across payments, accounts, onboarding, and merchant activity
• Design and run experiments to optimise fraud catch rates, false positives, and customer friction
• Partner with product and engineering teams to embed models into real-time decisioning systems
• Build features from high-volume transactional, device, network, and behavioural data
• Continuously monitor model performance, drift, and emerging fraud patterns
• Ensure data quality, governance, and responsible use of models in regulated environments
• Support investigations, strategy, and policy teams with advanced fraud analytics
• Mentor analysts and product teams on experimentation, detection strategy, and data-driven decision making

We would love to hear from you if…

• A strong foundation in statistics with a degree in a quantitative field (Statistics, Mathematics, Engineering, Computer Science, or similar)
• 5+ years of experience in data science, decision science, or risk analytics within fraud, payments, or financial crime
• Hands-on experience with fraud detection, transaction monitoring, or behavioural risk modelling
• Proficiency in SQL and at least one modelling/programming language (Python or R)
• Experience with machine learning, anomaly detection, network/graph features, and real-time decision systems
• Strong intuition for fraud typologies, adversarial behaviour, and evolving attack patterns
• Ability to translate complex analysis into clear, actionable recommendations for technical and non-technical stakeholders
• High ownership mindset and comfort working in fast-paced, cross-functional product environments

What we can offer you

• Culture: We put our people first and prioritize the well-being of every team member. We’ve built a company where all opinions carry weight and where all voices are heard. We value and respect each other and always look out for one another. Above all, we are human.
• Learning: We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks.
• Compensation: You’ll receive an attractive salary, pension, health insurance, monthly bonuses, plus other benefits

What to expect in the hiring process

• A preliminary phone call with the recruiter
• A coding exercise on HackerRank – covering core data science theory (math, statistics, linear algebra) and Python fundamentals (data structures & algorithms).
• A take-home assignment
• A technical interview with a Lead in our Data Science Team to review your take-home assignment in depth
• A behavioural and technical interview with the hiring manager

Moniepoint is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates.