Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

We are looking for an exceptional Data Scientist to join the Data Search & Analytics team. In this role, you will work directly with the Research and Trading desks to improve their productivity and efficiency.  

Your future role within QRT  

This team is integral to the firm’s success. As such, your responsibilities will include:  

• Sourcing, designing and onboarding new datasets according to trading desks’ priorities  
• Becoming an expert on QRT’s internal tools to help the relevant desks efficiently, using data in production of trading systems  
• Proactively solving data related problems in order to minimise time to production  
• Managing the full lifecycle of data sourcing projects, which includes data acquisition/exploration/engineering, prototyping and production  

Your present skillset  

• 3+ years of experience as a Data Scientist (or similar position); experience in a buy-side quantitative finance role is advantageous
• Postgraduate degree in a quantitative discipline such as Mathematics, Physics or Engineering.
• Advanced programming experience in Python, including proficiency with data handling libraries such as Pandas and NumPy
• Demonstratable interest in financial markets and the application of data in its analysis and understanding
• Experience working with both traditional and alternative financial datasets
• Excellent communication skills, with the ability to effectively collaborate with all stakeholders, including researchers, traders, engineers, management, and external vendors
• Ability to work in a high-performance, high-velocity environment

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

What You Will Do

At Doctolib, we're revolutionizing healthcare delivery through advanced AI systems focused on medical reasoning. As a Senior Staff Research Scientist, you'll develop cutting-edge AI solutions that enhance clinical decision-making and support healthcare professionals in their daily practice. You'll work at the intersection of machine learning and healthcare, creating models that can understand medical knowledge, reason through complex clinical scenarios, and assist medical practitioners in providing better care.

Your responsibilities include (but are not limited to):

• Solve Real-World Healthcare Challenges: Design and build advanced machine learning models, especially in NLP and large language models, to improve healthcare workflows, enhance patient experiences, and power intelligent health solutions at scale.
• Innovate & Experiment: Research and prototype novel algorithms and architectures, staying at the forefront of AI/ML developments. Bring new ideas from concept to working prototypes, leveraging the latest advances in deep learning and generative AI.
• Collaborate Across Teams: Work closely with product, engineering, medical experts, and other stakeholders to translate business needs into impactful research projects. Communicate technical concepts and results clearly to both technical and non-technical audiences.
• Drive Impact: Analyze large, complex data sets to extract actionable insights, define key metrics, and rigorously evaluate model performance.
• Share & Learn: Advance Doctolib’s AI expertise by sharing findings within the team and with the wider ML community through publications, talks, and workshops. Mentor and support other scientists and engineers in adopting best practices.

Who You Are

• Technical Expertise:
• PhD or Master’s degree (plus significant experience) in Computer Science, Machine Learning, Mathematics, or a related field; Publications as first author in top-tier AI/ML conferences such as NeurIPS, ICLR, ICML, ACL, EMNLP, or relevant medical informatics venues are a plus;
• Deep understanding of machine learning and deep learning concepts, with hands-on experience in NLP, LLMs, or generative AI.
• Strong programming skills in Python (and ideally experience with ML frameworks such as PyTorch or JAX).
• Familiarity with modern data tools and scalable training on large datasets.
• Innovator & Problem Solver:
• Track record of independently driving research and translating it into real-world applications.
• Experience designing experiments, evaluating intrinsic and extrinsic metrics, and iterating quickly.
• Curiosity and drive to learn, research, and apply new machine learning techniques.
  
  
• Collaborative & Communicative:
• Comfortable working in highly cross-functional teams, with the ability to clearly communicate complex concepts to diverse audiences.
• Passionate about sharing knowledge and contributing to a culture of learning and innovation.
  
  
• Mission-Driven:
• Motivated by Doctolib’s mission to make healthcare better for all. Eager to solve meaningful problems with technology.
• Detail-oriented, rigorous, and committed to delivering high-quality, production-ready solutions.

What we offer 

• Free comprehensive health insurance for you and your children

• 25 days of paid vacation per year, plus up to 14 days of RTT

• Free mental health and coaching services through our partner Moka.care

• Work from abroad for up to 10 days per year thanks to our flexibility days policy

• Lunch vouchers (Swile card) worth €8.50 per working day, with €4.50 covered by Doctolib

• A subsidy from the work council to refund part of the membership to a sport club or a creative class

• 50% reimbursement of your public transport subscription

• Parent Care Program: receive one additional month of leave on top of the legal parental leave

• For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support

• Relocation support in case of international mobility

• Access to the best AI tools for coding, development and dedicated training

 The interview process  

• HR Screen 
• Call with Research Team Member 30 mins
• Scientific Presentation + Case Study 1 hour 30mins
• Behavioral Interview 1 hour 15mins
• At least one Reference check 

 Job details 

• Permanent position 
• Full Time
• Location: Doctolib Paris office in Levallois Perret
• Work mode: Hybrid (3 days/week in the office)
• Start date: ASAP

If you would like to find out more about tech life at Doctolib, feel free to read our latest Medium blog articles!

At Doctolib, we are committed to improving access to healthcare for everyone. This translates into our recruitment process. We evaluate candidates based solely on qualifications and motivation, without any form of discrimination.

The more diverse ideas are heard, the more our product will truly improve healthcare for all. You are welcome to apply to Doctolib, regardless of your gender, religion, age, sexual orientation, ethnicity, disability.

To ensure equal opportunities, we invite you to exclude personal information (e.g. pictures, age) from your applications. If you require any accommodation, please let us know for support during the hiring process.

Join us in building the healthcare we all dream of!

All information provided is processed by Doctolib for application management. For data processing details, click here. Please contact hr.dataprivacy(at)doctolib.com for inquiries or to exercise your rights.

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products.

Building on our track record of AI-powered solutions (e.g., Bits AI, Bits Evolve, and our time series foundation model), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security.

We are focused on two research areas:

1. World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents.
2. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost.

What You'll Do:

• Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability
• Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure
• Design and build simulated environments and RL training loops for on-policy agent training and evaluation
• Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products
• Stay at the forefront of foundation models, world models, and RL-based agent research
• Contribute to research publications, present at top-tier conferences (e.g., NeurIPS, ICLR, ICML), and help open-source key model artifacts and benchmarks

Who You Are:

• You hold a PhD in Computer Science, Machine Learning, or a related field, with deep expertise in areas like generative modeling, world models, AI agents, reinforcement learning, or multimodal learning (or have equivalent experience)
• You have extensive experience designing and implementing deep learning models and agents, with a strong background in distributed training frameworks (e.g., DeepSpeed, Megatron-LM) and ML libraries (PyTorch)
• You have a track record of impactful publications at top-tier venues (e.g., NeurIPS, ICLR, ICML, TMLR)
• You are familiar with efficient training, post-training, and inference techniques for large foundation models
• You can explain complex models and research findings to both technical and non-technical audiences

Bonus Points (any of the following):

• Experience bridging research and real-world product applications, especially with large foundation models, world models, or RL-trained agents
• Passion for pushing the boundaries of AI with a focus on customer impact and scalable deployment
• Experience writing production data pipelines and applications
• Hands-on experience with GPU programming and optimization, including CUDA

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.

Benefits and Growth:

• Competitive global benefits 
• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Opportunity to collaborate closely with colleagues across the Datadog offices in New York City and Paris
• Opportunity to attend and present at conferences and meetups
• Intra-departmental mentor and buddy program for in-house networking
• An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

About Datadog: 

Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers’ entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center.

Equal Opportunity at Datadog:

Datadog is an Affirmative Action and Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference.

Your Privacy:

Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice.

#LI-Hybrid

The Applied AI team designs and builds algorithmically driven features in the Datadog app. We work across a range of applications, primarily focusing on analysis on streaming data such as anomaly detection, error outliers and faulty deployment analysis.  As an Applied Scientist you will work on building models and algorithms for machine learning powered features within the Datadog platform. You will work closely with our engineering and product partners to explore, build, scale and deliver these features that we incubate within the Applied AI team.

At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them.

What You’ll Do: 

• Design solutions for our different use cases. You will research and benchmark relevant   algorithms to find the best fit for our use-cases
• Leverage machine learning algorithms and statistical techniques to build new scalable product features
• Develop, deploy and monitor new and existing features to production
• Participate in our journal club by reading and presenting the latest academic research papers to the team
• Explore, analyze and tell the story behind high volumes of data flowing through Datadog systems 
• Maintain and monitor the models, services and infrastructure owned by your team
• Participate in your team’s on-call rotation

Who You Are: 

• You have a BS/MS/PhD in a Computer Science, Engineering, Machine Learning or related scientific field or equivalent experience
• You have experience working with high-scale systems and datasets including building models, applying machine learning to real business problems, and writing production data pipelines
• You can explain complex ideas and algorithms to non-technical audiences
• You care about code simplicity and performance
• You are excited to work on a user-facing product

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. 

Benefits and Growth: 

• Competitive global benefits
• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Opportunity to collaborate closely with colleagues across the Datadog offices in New York City and Paris
• Opportunity to attend and present at conferences and meetups
• Intra-departmental mentor and buddy program for in-house networking
• An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

#LI-Hybrid

Who we are

Artefact is a French consulting and engineering firm specializing in data and AI, and a leader in Europe. Headquartered in Paris, we are now present in 23 countries across all continents, with a team of 1,700 employees.

Our mission is to help businesses unlock the full potential of AI and data by developing tailor-made solutions that address their specific industry challenges. As pioneers in this field, we combine technological expertise with operational excellence, working alongside the world’s leading market players. Our clients span all key economic sectors - industry, retail, luxury, consumer goods, healthcare, and finance - and include major international corporations.

Beyond consulting, we are deeply committed to making AI ethical and accessible. We launched the Artefact School of Data to facilitate career transitions into tech roles and established AI Research Centers in Paris and Shanghai.

What you will be doing - Key responsibilities

As a Senior Data Scientist, you will play a key role in designing, delivering, and scaling AI solutions for our clients. You will be responsible for ensuring technical excellence while mentoring less experienced data scientists and acting as a trusted advisor for business stakeholders.

Your main responsibilities will include:

Delivering end-to-end AI projects

• Frame use cases with business teams, validate data availability, and define the right approach.
• Design and implement machine learning or generative AI solutions that create measurable business impact.
• Ensure solutions are robust, scalable, and production-ready by applying software engineering and MLOps best practices.

Driving technical excellence

• Translate business requirements into robust AI pipelines and architectures.
• Promote best practices in coding, testing, and deployment to guarantee maintainability and scalability.
• Explore and apply advanced AI techniques to solve complex client problems.

Being a trusted advisor for clients and teams

• Explain AI approaches in clear and pragmatic terms, highlighting feasibility, risks, and ROI.
• Build strong relationships with client stakeholders, from operational teams to managers.
• Act as a go-to expert for technical guidance within projects.

Contributing to team and knowledge development

• Mentor junior data scientists, provide feedback, and support their growth.
• Share best practices through workshops, documentation, and informal training sessions.
• Contribute to internal accelerators and tools to increase delivery efficiency across projects.
• Maintain active technology watch and bring new methods, tools, and frameworks into practice.

Qualifications - What we are looking for

• 3+ years of hands-on experience developing and deploying data-driven solutions.
• Strong knowledge in applied machine learning and generative AI.
• Solid understanding of software engineering and MLOps best practices.
• Experience delivering AI projects in cloud environments.

In addition to technical expertise, we value individuals who can:

• Show intellectual curiosity and structured problem-solving.
• Approach challenges with pragmatism and creativity.
• Bridge the gap between business stakeholders and technical teams.Deliver with autonomy and reliability, ensuring client satisfaction.Share knowledge and mentor more junior colleagues.Build trust with clients through clear communication and rigor.

Our recruitment process

1. HR call 
2. Standard Interview 
3. Technical Interview 
4. Fit Interview

At Artefact, we recruit our employees only on the basis of our needs and the individual qualities of each candidate. We ensure the development of their professional skills and responsibilities without discrimination of any kind, including belief, gender, age, disability, ethnic origin, sexual orientation, membership of a political organization, religion, trade union or minority group.

Who we are

Artefact is a French consulting and engineering firm specializing in data and AI, and a leader in Europe. Headquartered in Paris, we are now present in 23 countries across all continents, with a team of 1,700 employees.

Our mission is to help businesses unlock the full potential of AI and data by developing tailor-made solutions that address their specific industry challenges. As pioneers in this field, we combine technological expertise with operational excellence, working alongside the world’s leading market players. Our clients span all key economic sectors - industry, retail, luxury, consumer goods, healthcare, and finance - and include major international corporations.

Beyond consulting, we are deeply committed to making AI ethical and accessible. We launched the Artefact School of Data to facilitate career transitions into tech roles and established AI Research Centers in Paris and Shanghai.

What you will be doing - Key responsibilities

As a Senior Data Scientist, you will play a key role in designing, delivering, and scaling AI solutions for our clients. You will be responsible for ensuring technical excellence while mentoring less experienced data scientists and acting as a trusted advisor for business stakeholders.

Your main responsibilities will include:

Delivering end-to-end AI projects

• Frame use cases with business teams, validate data availability, and define the right approach.
• Design and implement machine learning or generative AI solutions that create measurable business impact.
• Ensure solutions are robust, scalable, and production-ready by applying software engineering and MLOps best practices.

Driving technical excellence

• Translate business requirements into robust AI pipelines and architectures.
• Promote best practices in coding, testing, and deployment to guarantee maintainability and scalability.
• Explore and apply advanced AI techniques to solve complex client problems.

Being a trusted advisor for clients and teams

• Explain AI approaches in clear and pragmatic terms, highlighting feasibility, risks, and ROI.
• Build strong relationships with client stakeholders, from operational teams to managers.
• Act as a go-to expert for technical guidance within projects.

Contributing to team and knowledge development

• Mentor junior data scientists, provide feedback, and support their growth.
• Share best practices through workshops, documentation, and informal training sessions.
• Contribute to internal accelerators and tools to increase delivery efficiency across projects.
• Maintain active technology watch and bring new methods, tools, and frameworks into practice.

Qualifications - What we are looking for

• 3+ years of hands-on experience developing and deploying data-driven solutions.
• Strong knowledge in applied machine learning and generative AI.
• Solid understanding of software engineering and MLOps best practices.
• Experience delivering AI projects in cloud environments.

In addition to technical expertise, we value individuals who can:

• Show intellectual curiosity and structured problem-solving.
• Approach challenges with pragmatism and creativity.
• Bridge the gap between business stakeholders and technical teams.Deliver with autonomy and reliability, ensuring client satisfaction.Share knowledge and mentor more junior colleagues.Build trust with clients through clear communication and rigor.

Our recruitment process

1. HR call 
2. Standard Interview 
3. Technical Interview 
4. Fit Interview

At Artefact, we recruit our employees only on the basis of our needs and the individual qualities of each candidate. We ensure the development of their professional skills and responsibilities without discrimination of any kind, including belief, gender, age, disability, ethnic origin, sexual orientation, membership of a political organization, religion, trade union or minority group.

Who we are

Artefact is a French consulting and engineering firm specializing in data and AI, and a leader in Europe. Headquartered in Paris, we are now present in 23 countries across all continents, with a team of 1,700 employees.

Our mission is to help businesses unlock the full potential of AI and data by developing tailor-made solutions that address their specific industry challenges. As pioneers in this field, we combine technological expertise with operational excellence, working alongside the world’s leading market players. Our clients span all key economic sectors - industry, retail, luxury, consumer goods, healthcare, and finance - and include major international corporations.

Beyond consulting, we are deeply committed to making AI ethical and accessible. We launched the Artefact School of Data to facilitate career transitions into tech roles and established AI Research Centers in Paris and Shanghai.

What you will be doing - Key responsibilities

As a Senior Data Scientist, you will play a key role in designing, delivering, and scaling AI solutions for our clients. You will be responsible for ensuring technical excellence while mentoring less experienced data scientists and acting as a trusted advisor for business stakeholders.

Your main responsibilities will include:

Delivering end-to-end AI projects

• Frame use cases with business teams, validate data availability, and define the right approach.
• Design and implement machine learning or generative AI solutions that create measurable business impact.
• Ensure solutions are robust, scalable, and production-ready by applying software engineering and MLOps best practices.

Driving technical excellence

• Translate business requirements into robust AI pipelines and architectures.
• Promote best practices in coding, testing, and deployment to guarantee maintainability and scalability.
• Explore and apply advanced AI techniques to solve complex client problems.

Being a trusted advisor for clients and teams

• Explain AI approaches in clear and pragmatic terms, highlighting feasibility, risks, and ROI.
• Build strong relationships with client stakeholders, from operational teams to managers.
• Act as a go-to expert for technical guidance within projects.

Contributing to team and knowledge development

• Mentor junior data scientists, provide feedback, and support their growth.
• Share best practices through workshops, documentation, and informal training sessions.
• Contribute to internal accelerators and tools to increase delivery efficiency across projects.
• Maintain active technology watch and bring new methods, tools, and frameworks into practice.

Qualifications - What we are looking for

• 3+ years of hands-on experience developing and deploying data-driven solutions.
• Strong knowledge in applied machine learning and generative AI.
• Solid understanding of software engineering and MLOps best practices.
• Experience delivering AI projects in cloud environments.

In addition to technical expertise, we value individuals who can:

• Show intellectual curiosity and structured problem-solving.
• Approach challenges with pragmatism and creativity.
• Bridge the gap between business stakeholders and technical teams.Deliver with autonomy and reliability, ensuring client satisfaction.Share knowledge and mentor more junior colleagues.Build trust with clients through clear communication and rigor.

Our recruitment process

1. HR call 
2. Standard Interview 
3. Technical Interview 
4. Fit Interview

At Artefact, we recruit our employees only on the basis of our needs and the individual qualities of each candidate. We ensure the development of their professional skills and responsibilities without discrimination of any kind, including belief, gender, age, disability, ethnic origin, sexual orientation, membership of a political organization, religion, trade union or minority group.

Locations:

• Europe: Paris / UK / Germany / Remote (EU)

About the role

We are looking for a scientifically credentialed strategist to lead the post-sales journey for our pharmaceutical partners. In this role, you will be the bridge between our cutting-edge foundational models and the R&D pipelines of the world’s leading biopharma companies.

You will use your deep expertise in machine learning and computational biology to build credibility with stakeholders, identify new opportunities for model application within their pipelines, and translate customer feedback into our product roadmap.

What you'll be doing

As our Applied AI Scientist (Pharma Partnerships) you are the primary architect of value for our most critical pharmaceutical partnerships. You will operate at the intersection of computational biology, ML and commercial scale across two strategic domains:

1. Partnership Value Realisation & Growth

• Post-Signature Leadership: Orchestrate the partner journey immediately following contract execution. You will act as the Project Manager for the deployment, ensuring seamless onboarding and integration of our foundational models.
• Scientific & technical thought-leadership: Consult with client R&D teams (ranging from bench scientists and data science teams to Heads of R&D) to diagnose their specific therapeutic challenges. Identify key use cases where our AI foundation models can unlock high value to our customers research and therapeutic priorities.
• Commercial Adoption & Growth: Proactively identify opportunities to expand the scope of the partnership. Leverage your understanding of the client’s pipeline to suggest new use cases, therapeutic areas, or departments where our technology can drive value.

2. Product Intelligence & Roadmap Influence

• Voice of the Customer: Synthesize technical feedback and performance metrics from the field. Translate complex biopharma user requirements into actionable technical specifications for our internal Research and Product teams. Identify high value opportunities to enrich our model capabilities and biology applications offering.
• Gap Analysis: Collaborate with our machine learning engineers to identify data modalities or functional gaps in our current offering, directly influencing future product iterations.

What you'll bring

The successful candidate will have a ‘team-first’ attitude; be independent, curious, and detail-oriented; thrive in a dynamic, fast-paced environment; and be fun to work with. We value individuals who bring deep domain expertise in computational biology, ML and pharmaceutical R&D alongside strong hands-on business development skills.

Scientific & Technical Credibility

• Educational Background: PhD in Computational Biology, Machine Learning, Bioinformatics, Genomics, or a related field is required.
• Domain Expertise: Deep understanding of the biopharma R&D value chain (target discovery to clinical trials). You understand the specific pain points of drug developers and are able to translate ambiguous biopharma use cases into rigorous ML applications.
• Technical Fluency:
• Deep experience in biological data modalities, notably multi-omics (single-cell, transcriptomics, proteomics) and histopathology slides.
• Extensive knowledge in modern ML architectures and paradigms like Transformers (ViT), GNNs, foundation models with embedding-based prediction heads (e.g., ABMIL), interpretability methods, and model evaluation & validation principles.
• Proven experience in designing end-to-end ML solutions for complex biological problems, including problem framing, data strategy and model design & evaluation
• Strong fluency in Python and deep learning frameworks (PyTorch, JAX)

Relationship & Strategic Skills

• Stakeholder Management: Proven experience navigating complex, matrixed organizations (Big Pharma experience is a plus). You can present to a VP of R&D in the morning and troubleshoot with a bioinformatician in the afternoon.
• Consulting Mindset: You are not just a support agent; you are a trusted advisor. You have experience in roles such as Field Application Scientist (FAS), Solution Architecture, or Scientific Consulting.
• Feedback Synthesis: Ability to distill complex client complaints or requests into clear, prioritized product requirements.

How to stand out:

• Experience in a startup or innovative environment, showing adaptability and proactiveness.
• A strong existing network within Global Top 20 Pharma R&D.
• Experience specifically with "Foundation Models" or Generative AI in a biological context.
• Track record of high-impact publications (Nature, Cell, NeurIPS).

The candidate journey

To be considered, please submit your CV in English.

We believe in a transparent and collaborative interview process. We need to find a fit for both you and the company. Here is what you can expect after submitting your application:

• Screening: Once you have applied, the hiring team will review your application. If your experience and skills align with the role, you will be invited to a 30-minute introductory call with the Hiring Manager to discuss your background, motivations, and the position in more detail.
• Interviews: Following a successful screening, you will be invited to a series of interviews:
  • Case Study (60 min): You will prepare a mock kick-off document for a client engagement with us to evaluate the model on their desired use-cases, including suggesting interesting use cases for our model and outlining the project plan. We want to see how well you understand the potential use cases for foundation models in the clinical stage of pharma development cycles, and how you would manage a key strategic partner through the deployment and delivery process.
  • Scientific Deep Dive Presentation (30 min): You will briefly present a piece of scientific work to a small panel of our researchers and engineers, led by a senior member of our technical team, and answer Q&S after (10-15 min presentation, 15-20 min Q&A). The content is up to you: it can be your own past research, a relevant paper in the field, or extra points if it’s a specific Bio-AI use case you’ve worked on with a biopharma. The goal is to assess your technical fluency, your ability to facilitate scientific debate, and how you communicate complex concepts to experts.
  • Executive Interview (30 min): A comprehensive discussion with member(s) of our Senior Leadership. This session moves beyond technical competency to focus on long-term vision, values, and mutual potential. This is an opportunity for you to get to know the company better as well.
• Offer: Following the completion of all interviews, our hiring team will make a final decision and will be in touch to share the outcome. Please note that an offer is contingent upon the successful completion of a reference check.
• Onboarding: We are happy to have you joining the team! Once you have accepted and signed your offer, we will be in touch to begin the process of onboarding you.

Why this is a unique opportunity

• A collaborative and mission-driven work environment.
• Competitive salary and equity package.
• Flexible work arrangements, including remote options.
• Opportunities for professional growth and leadership development.
• Shape the future of biology and AI by contributing to groundbreaking work.

Research Scientist in Science

Founded in 2014, InstaDeep is today an EMEA leader in decision-making AI products for the Enterprise, with headquarters in London, and offices in Paris, Berlin, Tunis, Lagos, Dubai, Cape Town and the USA. InstaDeep has been named among the Top 100 global AI startups for three consecutive years by CB Insights, as well as one of the 100 most promising B2B companies in Europe, by Sifted. We have created an environment that ensures a challenge by working closely with a broad spectrum of high-quality clients, pushing you to thrive in an environment that’s rarely tedious and always looking to push you to come up with outside-the-box solutions using cutting-edge technologies. In our mission to stay ahead of the curve, we are proud to partner with firms such as BioNTech SE, Google DeepMind, NVIDIA and Intel, and world-class universities such as MIT, Oxford, UCL, and Imperial College London. We are also an NVIDIA Elite Service Delivery Partner and Google Cloud Partner.

Are you a Research Scientist in Science? You will contribute to knowledge in different fields, and plan and conduct experiments to help expand the canon of the company's scientific knowledge.

If so then keep reading…. 

As a Research Scientist in Science, you’ll be a part of the Research department, 

The Research Scientist in Science must accomplish the following:  

• Collaborate with other researchers and experts to develop machine-learning methods for problems in computational biology.
• Engage and assist in the identification of research directions
• Contribute to the design and implementation of models, tools and libraries to accelerate our research effort.
• Adapt neural network algorithms to deploy on supercomputing architectures to best exploit modern parallel environments 
• Report and present experimental results and research findings clearly and effectively, both internally and externally, verbally and in writing. 
• Contribute to the team’s publication efforts.
• Bridge the gap between the research and product teams by integrating new fundamental research into applied projects. 

Requirements:  

• Ph.D. degree in Computer Science, Machine Learning or a related field.
• Experience using Deep Learning frameworks such as PyTorch, Tensorflow and/or Jax.
• Experience in developing and debugging in Python3 or similar languages.
• Experience with high-performance computing methods and frameworks such as MPI, Ray (distribution on clusters of CPUs and accelerators)
• Experience in planning and conducting research works
• A demonstrated ability to successfully deliver high-quality research, including publishing scientific papers (ICLR, NeurIPS, ICML, etc).
• Excellent communication skills and collaborative spirit.

Nice to haves

• 2-5 years experience

• Software engineering experience demonstrated via previous work, and contributions to open source or coding competitions.
• Reinforcement Learning, Computer Vision, or Natural Language Processing experience.

Our Diversity, Equity, and Inclusion commitments

We empower individuals to celebrate their uniqueness here at InstaDeep. Our team comes from all walks of life, and we’re proud to continue encouraging and supporting applicants from underrepresented groups across the globe. Our commitment to creating an authentic environment comes from our ability to learn and grow from our diversity, and how better to experience this by other than by joining our team? 

At present, we operate in a hybrid work model of two days mandatory a week in the office. We are continuing to review the situation with the well-being of InstaDeepers at the forefront of our minds.

Right to work: Please note you will require the legal right to work in the location you are applying for. 

If you have any further questions please do not hesitate to contact us at: talent@instadeep.com

Who we are

Artefact is a French consulting and engineering firm specializing in data and AI, and a leader in Europe. Headquartered in Paris, we are now present in 23 countries across all continents, with a team of 1,700 employees.

Our mission is to help businesses unlock the full potential of AI and data by developing tailor-made solutions that address their specific industry challenges. As pioneers in this field, we combine technological expertise with operational excellence, working alongside the world’s leading market players. Our clients span all key economic sectors - industry, retail, luxury, consumer goods, healthcare, and finance - and include major international corporations.

Beyond consulting, we are deeply committed to making AI ethical and accessible. We launched the Artefact School of Data to facilitate career transitions into tech roles and established AI Research Centers in Paris and Shanghai.

What you will be doing - Key responsibilities

As a Manager Data Scientist, you will play a central role in the design, delivery and scaling of AI projects for our clients. Reporting to the CTO, your responsibilities will include:

• Leading end-to-end client projects: from framing use cases with business stakeholders to implementing AI solutions that generate measurable impact.
• Ensuring technical excellence: promote software engineering and MLOps best practices to deliver scalable solutions and bring them into production.
• Supporting solution design: challenging business requirements, validating data availability, and selecting the most appropriate methodologies and architectures.
• Being the technical reference for clients: explaining AI approaches in simple terms, providing recommendations on feasibility, risks, and ROI.
• Developing trusted client relationships: interacting with C-level and operational teams to position Artefact as a long-term partner on their Data & AI journey.

Beyond these core responsibilities, you will also be involved in:

Managing the country’s data science team

• Support team staffing, ensuring the right skills are applied to meet project needs.
• Ensure each individual’s continuous well-being within the team, supporting their growth through mentoring, coaching, and career development plans.
• Help define the team’s career framework and participate in performance review processes.
• Challenge existing ways of working and drive innovation to continuously improve Artefact’s data science team.

Developing Artefact’s technical expertise

• Contribute to testing and implementing advanced AI approaches and emerging techniques on client use cases.
• Drive initiatives to build internal accelerators, such as modules and tools that can be reused across projects.
• Maintain an active technology watch: evaluate emerging tools, frameworks, and cloud services to assess how they can address client needs.
• Share knowledge through workshops, informal training sessions, and documentation, fostering a culture of continuous learning.

Being a great tech manager

• Lead by example: demonstrate technical rigor, pragmatic problem-solving, and the ability to step in directly on projects when the team needs support.
• Provide constructive feedback to help data scientists in your team progress in both technical and consulting dimensions.
• Anticipate risks and unblock teams, ensuring projects stay on track.
• Balance ambition and feasibility: critically assess approaches, driving innovation while ensuring solutions stay realistic to deliver.
• Foster collaboration between data scientists, data engineers, and business teams to ensure solutions are effectively integrated and adopted.

Qualifications - What we are looking for

• 5+ years of hands-on experience developing data-driven solutions.
• Strong knowledge in applied machine learning and generative AI.
• Solid understanding of software engineering and MLOps best practices.
• Experience with industrializing AI workflows in cloud environments.

In addition to technical expertise, we value individuals who can:

• Lead teams, manage stakeholders, and deliver impactful projects in a business context.
• Show intellectual curiosity and excellent problem-solving skills.
• Tackle challenges with pragmatism and creativity.
• Support growth, mentoring juniors and constructively challenging seniors.
• Earn trust from both peers and business stakeholders.

 Our recruitment process

1. HR call 
2. Standard Interview 
3. Technical Interview 
4. Fit Interview

At Artefact, we recruit our employees solely on the basis of our needs and the individual qualities of each candidate. We ensure the development of their professional skills and responsibilities without discrimination of any kind, including belief, gender, age, disability, ethnic origin, sexual orientation, membership of a political organization, religion, trade union or minority group.

Who we are

Artefact is a French consulting and engineering firm specializing in data and AI, and a leader in Europe. Headquartered in Paris, we are now present in 23 countries across all continents, with a team of 1,700 employees.

Our mission is to help businesses unlock the full potential of AI and data by developing tailor-made solutions that address their specific industry challenges. As pioneers in this field, we combine technological expertise with operational excellence, working alongside the world’s leading market players. Our clients span all key economic sectors - industry, retail, luxury, consumer goods, healthcare, and finance - and include major international corporations.

Beyond consulting, we are deeply committed to making AI ethical and accessible. We launched the Artefact School of Data to facilitate career transitions into tech roles and established AI Research Centers in Paris and Shanghai.

What you will be doing - Key responsibilities

As a Manager Data Scientist, you will play a central role in the design, delivery and scaling of AI projects for our clients. Reporting to the CTO, your responsibilities will include:

• Leading end-to-end client projects: from framing use cases with business stakeholders to implementing AI solutions that generate measurable impact.
• Ensuring technical excellence: promote software engineering and MLOps best practices to deliver scalable solutions and bring them into production.
• Supporting solution design: challenging business requirements, validating data availability, and selecting the most appropriate methodologies and architectures.
• Being the technical reference for clients: explaining AI approaches in simple terms, providing recommendations on feasibility, risks, and ROI.
• Developing trusted client relationships: interacting with C-level and operational teams to position Artefact as a long-term partner on their Data & AI journey.

Beyond these core responsibilities, you will also be involved in:

Managing the country’s data science team

• Support team staffing, ensuring the right skills are applied to meet project needs.
• Ensure each individual’s continuous well-being within the team, supporting their growth through mentoring, coaching, and career development plans.
• Help define the team’s career framework and participate in performance review processes.
• Challenge existing ways of working and drive innovation to continuously improve Artefact’s data science team.

Developing Artefact’s technical expertise

• Contribute to testing and implementing advanced AI approaches and emerging techniques on client use cases.
• Drive initiatives to build internal accelerators, such as modules and tools that can be reused across projects.
• Maintain an active technology watch: evaluate emerging tools, frameworks, and cloud services to assess how they can address client needs.
• Share knowledge through workshops, informal training sessions, and documentation, fostering a culture of continuous learning.

Being a great tech manager

• Lead by example: demonstrate technical rigor, pragmatic problem-solving, and the ability to step in directly on projects when the team needs support.
• Provide constructive feedback to help data scientists in your team progress in both technical and consulting dimensions.
• Anticipate risks and unblock teams, ensuring projects stay on track.
• Balance ambition and feasibility: critically assess approaches, driving innovation while ensuring solutions stay realistic to deliver.
• Foster collaboration between data scientists, data engineers, and business teams to ensure solutions are effectively integrated and adopted.

Qualifications - What we are looking for

• 5+ years of hands-on experience developing data-driven solutions.
• Strong knowledge in applied machine learning and generative AI.
• Solid understanding of software engineering and MLOps best practices.
• Experience with industrializing AI workflows in cloud environments.

In addition to technical expertise, we value individuals who can:

• Lead teams, manage stakeholders, and deliver impactful projects in a business context.
• Show intellectual curiosity and excellent problem-solving skills.
• Tackle challenges with pragmatism and creativity.
• Support growth, mentoring juniors and constructively challenging seniors.
• Earn trust from both peers and business stakeholders.

 Our recruitment process

1. HR call 
2. Standard Interview 
3. Technical Interview 
4. Fit Interview

At Artefact, we recruit our employees solely on the basis of our needs and the individual qualities of each candidate. We ensure the development of their professional skills and responsibilities without discrimination of any kind, including belief, gender, age, disability, ethnic origin, sexual orientation, membership of a political organization, religion, trade union or minority group.

Who we are

Artefact is a French consulting and engineering firm specializing in data and AI, and a leader in Europe. Headquartered in Paris, we are now present in 23 countries across all continents, with a team of 1,700 employees.

Our mission is to help businesses unlock the full potential of AI and data by developing tailor-made solutions that address their specific industry challenges. As pioneers in this field, we combine technological expertise with operational excellence, working alongside the world’s leading market players. Our clients span all key economic sectors - industry, retail, luxury, consumer goods, healthcare, and finance - and include major international corporations.

Beyond consulting, we are deeply committed to making AI ethical and accessible. We launched the Artefact School of Data to facilitate career transitions into tech roles and established AI Research Centers in Paris and Shanghai.

What you will be doing - Key responsibilities

As a Manager Data Scientist, you will play a central role in the design, delivery and scaling of AI projects for our clients. Reporting to the CTO, your responsibilities will include:

• Leading end-to-end client projects: from framing use cases with business stakeholders to implementing AI solutions that generate measurable impact.
• Ensuring technical excellence: promote software engineering and MLOps best practices to deliver scalable solutions and bring them into production.
• Supporting solution design: challenging business requirements, validating data availability, and selecting the most appropriate methodologies and architectures.
• Being the technical reference for clients: explaining AI approaches in simple terms, providing recommendations on feasibility, risks, and ROI.
• Developing trusted client relationships: interacting with C-level and operational teams to position Artefact as a long-term partner on their Data & AI journey.

Beyond these core responsibilities, you will also be involved in:

Managing the country’s data science team

• Support team staffing, ensuring the right skills are applied to meet project needs.
• Ensure each individual’s continuous well-being within the team, supporting their growth through mentoring, coaching, and career development plans.
• Help define the team’s career framework and participate in performance review processes.
• Challenge existing ways of working and drive innovation to continuously improve Artefact’s data science team.

Developing Artefact’s technical expertise

• Contribute to testing and implementing advanced AI approaches and emerging techniques on client use cases.
• Drive initiatives to build internal accelerators, such as modules and tools that can be reused across projects.
• Maintain an active technology watch: evaluate emerging tools, frameworks, and cloud services to assess how they can address client needs.
• Share knowledge through workshops, informal training sessions, and documentation, fostering a culture of continuous learning.

Being a great tech manager

• Lead by example: demonstrate technical rigor, pragmatic problem-solving, and the ability to step in directly on projects when the team needs support.
• Provide constructive feedback to help data scientists in your team progress in both technical and consulting dimensions.
• Anticipate risks and unblock teams, ensuring projects stay on track.
• Balance ambition and feasibility: critically assess approaches, driving innovation while ensuring solutions stay realistic to deliver.
• Foster collaboration between data scientists, data engineers, and business teams to ensure solutions are effectively integrated and adopted.

Qualifications - What we are looking for

• 5+ years of hands-on experience developing data-driven solutions.
• Strong knowledge in applied machine learning and generative AI.
• Solid understanding of software engineering and MLOps best practices.
• Experience with industrializing AI workflows in cloud environments.

In addition to technical expertise, we value individuals who can:

• Lead teams, manage stakeholders, and deliver impactful projects in a business context.
• Show intellectual curiosity and excellent problem-solving skills.
• Tackle challenges with pragmatism and creativity.
• Support growth, mentoring juniors and constructively challenging seniors.
• Earn trust from both peers and business stakeholders.

 Our recruitment process

1. HR call 
2. Standard Interview 
3. Technical Interview 
4. Fit Interview

At Artefact, we recruit our employees solely on the basis of our needs and the individual qualities of each candidate. We ensure the development of their professional skills and responsibilities without discrimination of any kind, including belief, gender, age, disability, ethnic origin, sexual orientation, membership of a political organization, religion, trade union or minority group.

About DV & Scibids

"DV Scibids" is a global leader in AI-powered digital campaign activation. Scibids' solutions empower global brands to effectively boost ad performance and outcomes while improving operational efficiency and reducing manual lift. DoubleVerify technology does not rely on digital identifiers such as cookies and can be activated across leading Demand-Side Platforms such as The Trade Desk, DV360, and Xandr to mention a few. To learn more visit https://doubleverify.com/scibids-ai/

DV Scibids' AI Optimisation technology equips these trading desks with machine learning solutions which use real-time performance data to discover the optimal amount to bid for each advertising opportunity, thus delivering the final advertisers significant lifts in performance and productivity. The technology developed by Scibids is rooted in a solid scientific and market expertise and now has a team of 30+ Data Scientists based in our Paris office, working alongside DV's global engineering and data science org.

About the Role

The mission of Scibids AI is to provide media buyers with fully automated buying strategies for display campaigns, leading to incomparable performances for a minimum of human work. 

As a Senior Data Scientist, you will help shape and strengthen the Scibids DoubleVerify bidding algorithms — the central intelligence behind our platform. You will drive the evolution of our automation framework, transforming unmet business cases into scalable product enhancements. This role blends rigorous statistical thinking with hands-on implementation, demanding both intellectual precision and practical execution.

This position will combine high development standards, a relentless curiosity, a strong understanding of DV's business priorities and the ambition for your work to become a real game changer!

On a day to day basis, your responsibilities will include:

• Managing projects end-to-end, taking ownership from the initial proof-of-concept phase through to production deployment and monitoring.
• Mentoring junior developers, providing technical guidance, conducting code reviews, and sharing best practices to ensure high code quality.
• Working with massive datasets (billions of ad impressions/month) and millions of variables.
• Solving non-routine analysis problems (not handled by off-the-shelf ML solvers).
• Solving challenging scaling/engineering problems as our system produces thousands of ML models per day.
• Working closely with the commercial and customer success teams to help identify business cases where a new algorithm is needed or existing ones need improvement.
• Identifying and automating any repetitive process taking place at Scibids, including cases where this means developing some AI routines replacing “human common sense.”
  
  

Qualifications

Minimum qualifications:

• MS degree in applied mathematics or data science (e.g., statistics, probabilities, operations research, machine learning).
• 2 to 5 years of professional experience in Data Science with Python/C++.
• Passion for automation and data-driven decisions.

Preferred qualifications:

• Proven professional experience in a SQL-like language.
• Experience deploying machine learning models into production environments.
• Previous experience leading technical projects or mentoring team members.
  
  

Technical stack relevant to the position

• Python
• SQL
• Kubernetes, Docker, Github
• Google Cloud Environment, App Engine Standard, Cloud SQL, Google Cloud Datastore...

Others

• Contract type: full-time position (French “CDI”).
• Based in Paris (75008) – Champs-Elysées
• Preferred availability: ASAP
• Compensation: competitive package including fixed salary, annual bonus and company equity
• Exact figures depend on profile.

#Hybrid 

Vos missions

Doctolib développe des solutions innovantes pour améliorer l'accès aux soins et la qualité de vie des professionnels de santé. Dans le cadre de notre engagement pour une intelligence artificielle responsable, nous recherchons un.e stagiaire M2 pour évaluer les biais dans un système de dialogue en pédiatrie par l'analyse des conversations entre l'IA et les patients. 

En collaboration avec les data scientists de Doctolib et les chercheurs du LISN (Université Paris-Saclay), vous contribuerez à garantir l'équité et la fiabilité de nos solutions d'IA appliquées à la santé. L'un des objectifs clés de ce stage sera la création d'un jeu de données annoté et anonymisé qui sera publié en open-source. Ce stage de 5 mois vous permettra de travailler sur un projet à fort impact sociétal, à l'intersection du traitement automatique des langues, de la santé et de l'éthique de l'IA.

Vos responsabilités incluent, mais ne sont pas limitées à :

• Réaliser une revue de la littérature sur les méthodes d'évaluation des biais dans les modèles de langue appliqués à la santé
• Analyser un corpus de dialogues anonymisés entre le système d’IA et les parents/patients en pédiatrie pour identifier les biais potentiels
• Définir et mettre en œuvre un schéma d'annotation pour caractériser les biais identifiés
• Construire un cadre d'évaluation s'appuyant sur une évaluation désagrégée par caractéristiques démographiques
• Appliquer ce cadre au système de dialogue et comparer les résultats avec d'autres modèles auto-régressifs

Les qualités attendues

Avant de poursuivre votre lecture, si vous n'avez pas le profil exact décrit ci-dessous, mais que vous pensez que cette description de poste correspond à vos compétences et à vos aspirations, nous vous encourageons tout de même à postuler.

Vous pourrez être le prochain membre de notre équipe si vous :

• Maîtrisez Python et l'écosystème de traitement des données (pandas, scikit-learn)
• Êtes familier avec les modèles de langue et les bibliothèques associées (HuggingFace Transformers, vLLM ou équivalent)
• Possédez d'excellentes capacités de rédaction scientifique en français et en anglais
• Êtes en fin de Master 2 (professionnel ou recherche) ou d'école d'ingénieur
• Démontrez un intérêt pour les questions d'équité et de biais en intelligence artificielle

Ce serait fantastique si :

• Vous avez des connaissances en traitement automatique des langues, notamment en évaluation de modèles
• Vous possédez une expérience avec des cadres d'évaluation (benchmarks, métriques)
• Vous avez une sensibilité au domaine médical ou de la santé

Notre offre

• Des tickets restaurant d'une valeur de 8,5 € par jour, dont 4,5 € pris en charge par Doctolib
• Un programme d'intégration complet de 3 mois incluant la Doctolib Academy et diverses formations (langues, soft skills, compétences techniques)
• Une subvention du comité d'entreprise pour le remboursement partiel d'adhésions à des activités sportives ou de loisirs
• Un remboursement à 50% de l'abonnement aux transports en commun 

Le processus de recrutement

• Codingame en ligne
• Entretien avec notre Talent Recruiter (30 minutes)
• Entretien avec Nicolas, notre Principal Data Scientist (30 minutes)
• Entretien avec LISN (60 minutes)

Détails du poste

• Stage
• Temps Plein
• Levallois-Perret (Doctolib) et Orsay (LISN)
• Prise de poste : dès que possible
• Durée : 5 mois

Chez Doctolib, nous sommes convaincus que nous devons améliorer la santé pour tout le monde. Cela se reflète dans notre processus de recrutement. Nous évaluons les candidatures uniquement sur la base des qualifications et de la motivation, sans aucune forme de discrimination.

Plus les idées sont diverses, plus notre produit améliorera véritablement la santé pour tout le monde. Vous pouvez postuler chez Doctolib, quel que soit votre genre, religion, âge, orientation sexuelle, origine ethnique ou handicap.

Afin de garantir l'égalité des chances, nous vous invitons à exclure les informations personnelles (par exemple : photos, âge) de vos candidatures. Si vous avez besoin d'aménagements particuliers, merci de nous en informer pour que nous puissions adapter le processus de recrutement. Rejoignez-nous pour construire la santé dont nous rêvons tous !

Toutes les informations fournies sont traitées par Doctolib pour la gestion des candidatures. Pour plus de détails sur le traitement des données, cliquez ici. Veuillez contacter hr.dataprivacy(at)doctolib.com pour toute question ou pour exercer vos droits.

About the opportunity 

We are looking for a Senior Data Scientist to join a team of applied research.

The AI department currently consists of 50 people who are a mix of data scientists, machine learning and backend engineers.
The department provides technologies that power outcomes of campaigns with a total yearly turn over of $1.7B. 
Runs large scale prediction and control systems for ad delivery, dealing with millions of live ads, doing more than a billion predictions per second based on large on-line trained models being updated every 5 minutes.

What will you do?

As a Data Scientist, your mission will be to:

• Innovate at Scale: Stay at the forefront of AdTech research, focusing on CTR prediction, online learning regimes, and high-dimensional embeddings.
• Bridge Research & Engineering: Collaborate with cross-functional teams to identify research gaps and translate them into production-ready features.
• Own the Lifecycle: Lead the end-to-end process—from reading the latest ArXiv papers to A/B testing and monitoring model performance in a live environment.
• Experiment Freely: Dedicate time to "deep-work" sessions, testing unconventional hypotheses and new algorithmic approaches.

What will you bring to the team?

• The Foundation: An advanced degree (MSc/PhD) in a quantitative field or equivalent "in-the-trenches" industry experience.
• The Toolkit: 4–5 years of experience in applied research, specifically deploying ML algorithms into high-throughput online environments.
• The Hybrid Edge: Strong software engineering fundamentals; you don’t just design models, you understand how they fit into the code stack.
• Critical Thinking: The ability to dismantle a scientific paper, critique its methodology, and implement its core findings effectively.
• Communication: A knack for making the complex simple. You can explain a transformer-based ranking system to a peer or a product manager with equal clarity.

Please submit your CV in English.

We care about you 

• Career Development: Continuous investment in our employees’ skills: in-house and external training, internal mobility …
• Life Balance: A well-balanced work-life for our employees is one of our top priorities: 22 days off per year, hybrid work (3 days per week in the office)
• Wellness: Prioritizing employee well-being through premium work equipment, enjoyable work environment (work-life balance, team building events, summits), remote work subsidy, promoting Diversity & Inclusion with internal & external initiatives, etc. 

#LI-Hybrid

#LI-Hybrid

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 (Convention de stage) signed by your school or university for 6 months and you are able to start your internship on August 31th.
• 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.
• French is mandatory at a fluent level and you can communicate clearly in English.

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 : 2000€ 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.