23,933 Data Scientist Jobs (August 2026) - Apply with AI

Point72 is seeking an AI Data Scientist for its Data Services group, focusing on delivering precise data solutions for systematic Portfolio Managers. This role involves building AI-powered data products, developing AI/ML model pipelines, and collaborating with various teams to implement scalable AI solutions. Candidates should possess a PhD in Computer Science, programming proficiency in Python and SQL, and ideally have experience in the financial industry.

Posted 2 weeks ago

Join Bilue, a digital consultancy focused on delivering user-friendly technology solutions for prominent Australian businesses. As an AI Data Scientist, you will play a crucial role in ensuring the integrity of AI systems by managing data governance and knowledge management. Your work will focus on designing data catalogues, maintaining metadata schemas, and collaborating with engineers to enhance retrieval systems. Bilue values a people-first culture, emphasizing collaboration, curiosity, and professional growth while maintaining a flexible hybrid work environment.

Posted 3 weeks ago

dunnhumby is the global leader in Customer Data Science, partnering with the world’s most ambitious retailers and brands to put the customer at the heart of every decision. We combine deep insight, advanced technology, and close collaboration to help our clients grow, innovate, and deliver measurable value for their customers. dunnhumby employs nearly 2,500 experts in offices throughout Europe, Asia, Africa, and the Americas working for transformative, iconic brands such as Tesco, Coca-Cola, Nestlé, Unilever and Metro. We’re looking for an Applied Data Scientist who expects more from their career. It’s a chance to apply your expertise to distil complex problems into compelling insights using the best of machine learning and human creativity to deliver effective and impactful solutions for clients. Joining our advanced data science team, you’ll investigate, develop, implement and deploy a range of complex applications and components while working alongside super-smart colleagues challenging and rewriting the rules, not just following them. What we expect from you Degree in Statistics, Maths, Physics, Economics or similar field 2 to 4 years of experience required Programming skills (Python, ML, SQL are a must have) Analytical Techniques and Technology Logical thinking and problem solving Strong communication skills Experience with and passion for connecting your work directly to the customer experience, making a real and tangible impact Statistical Modelling and experience of applying data science into client problems. What you can expect from us We won’t just meet your expectations. We’ll defy them. So you’ll enjoy the comprehensive rewards package you’d expect from a leading technology company. But also, a degree of personal flexibility you might not expect. Plus, thoughtful perks, like flexible working hours and your birthday off. You’ll also benefit from an investment in cutting-edge technology that reflects our global ambition. But with a nimble, small-business feel that gives you the freedom to play, experiment and learn. And we don’t just talk about diversity and inclusion. We live it every day – with thriving networks including dh Gender Equality Network, dh Proud, dh Family, dh One, dh Enabled and dh Thrive as the living proof. We want everyone to have the opportunity to shine and perform at your best throughout our recruitment process. Please let us know how we can make this process work best for you. Our approach to Flexible Working At dunnhumby, we value and respect difference and are committed to building an inclusive culture by creating an environment where you can balance a successful career with your commitments and interests outside of work. We believe that you will do your best at work if you have a work / life balance. Some roles lend themselves to flexible options more than others, so if this is important to you please raise this with your recruiter, as we are open to discussing agile working opportunities during the hiring process. For further information about how we collect and use your personal information please see our Privacy Notice which can be found (here)

Posted 1 week ago

Nift is disrupting performance marketing, delivering millions of new customers to brands every month. We're hiring a hands-on Senior Applied Data Scientist to help build and scale production-grade recommendation systems that drive our core marketplace outcomes. This is not a research-only role . We're looking for someone who can take models from idea to production — running experiments, measuring business impact, and continuously improving the systems behind how Nift matches people with the right brands. You'll own the full lifecycle: exploratory analysis, data prep, modeling, testing, deployment, and post-launch measurement. The ideal candidate has worked in a real production environment, brings strong deep learning experience, and understands recommendation systems in practice — not just in theory. Success here means shipping models that move Nift's core KPIs, connecting technical work to measurable business impact, and helping the team scale with strong engineering discipline. This role is ideally based in Israel, but strong candidates in the U.S. will also be considered. What You'll Do Own the full funnel of applied machine learning work, from idea through production Build, improve, and deploy recommendation models that support Nift's core business goals Tackle deep learning problems in a production setting — not just offline experimentation Conduct exploratory data analysis, preprocessing, feature development, and modeling Run experiments and evaluate success against business KPIs, not just model metrics Partner with engineering and infrastructure teammates to productionize models and scale systems Improve recommendation quality, personalization, and the business performance tied to those systems What You'll Have 5+ years of experience in production data science environments Strong hands-on experience taking machine learning models into production Strong deep learning experience; proficiency with PyTorch or TensorFlow is expected Direct experience with recommendation systems, or adjacent experience in areas like bidding or dynamic pricing Strong Python and SQL skills Experience working with data at meaningful scale — high-scale environments are a strong plus The ability to measure model success through business outcomes such as revenue, conversion, churn, or similar KPIs Bonus points for: A Master's degree, especially paired with strong production experience A PhD paired with meaningful production-grade work (purely academic backgrounds aren't the target profile for this role) A software engineering background — particularly for candidates who've built pipelines and production systems before moving into machine learning About Us Our mission is to reshape how people discover and try new brands by introducing them to new products and services through thoughtful "thank-you" gifts. Our customer-first approach ensures businesses acquire new customers efficiently while making customers feel valued and rewarded. We are a data-driven, cash-flow-positive company that has experienced 731% growth over the last three years . Now we're scaling to become one of the largest sources of new customer acquisition worldwide. Backed by investors who supported Fitbit, Warby Parker, and Twitter, we're poised for exponential growth and ready to demonstrate impact on a global scale.

Posted 2 weeks ago

The Junior Data Scientist supports the design, development, and operationalization of machine learning, advanced analytics, and Generative AI solutions for ZainTECH’s enterprise customers. The role also supports customer-facing delivery activities, including workshops, demonstrations, and proof-of-concept engagements, while building the technical and consulting capabilities required to progress within ZainTECH’s Data AI Practice. Responsibilities: Machine Learning Data Science Develop, train, test, and evaluate machine learning models for classification, regression, forecasting, NLP, and other enterprise use cases under the guidance of senior team members. Perform data preparation, exploratory data analysis, feature engineering, and model evaluation to support the development of effective data science solutions. Build and maintain reproducible pipelines for data preparation, feature engineering, and model training. Apply statistical techniques and appropriate model evaluation methodologies to validate solution performance and business relevance. Generative AI Emerging Technologies Contribute to the development of Generative AI solutions using Large Language Models (LLMs) and foundation models. Support prompt engineering, embeddings, vector databases, Retrieval-Augmented Generation (RAG) pipelines, and LLM evaluation. Integrate foundation models, including Azure OpenAI and open-source LLMs, into enterprise applications and workflows. Gain hands-on experience with modern GenAI frameworks such as LangChain, LangGraph, and related technologies. Support the evaluation and continuous improvement of GenAI solutions based on performance, accuracy, and customer requirements. ModelOps Solution Operationalization Support the full machine learning model lifecycle, including experiment tracking, model versioning, packaging, deployment, monitoring, and retraining. Apply ModelOps/MLOps practices and tools such as MLflow, model registries, CI/CD pipelines, and containerized model serving. Monitor deployed models for drift, performance degradation, and data quality issues. Assist in developing monitoring, alerting, and remediation processes to maintain model performance in production environments. Collaborate with DevOps and engineering teams to support the reliable deployment and operation of AI solutions. Solution Development Integration Work closely with Data Engineers, ML Engineers, DevOps Engineers, and Application Developers to integrate models into end-to-end enterprise solutions. Support the development of APIs and lightweight applications to expose machine learning models and GenAI capabilities where required. Work with structured and unstructured data across different data sources and platforms. Contribute to solutions deployed across cloud and enterprise AI platforms, with a particular focus on Microsoft Azure. Customer Delivery Documentation Participate in customer workshops, demonstrations, and proof-of-concept engagements as part of the Data AI delivery team. Support senior team members in translating customer requirements into practical data science and AI solutions. Communicate technical findings and model outputs clearly to technical and non-technical stakeholders. Document solutions, experiments, methodologies, and operational runbooks to production standards. Contribute to knowledge-sharing and continuous improvement initiatives within the Data AI Practice. Our Culture Code of Conduct: At ZainTECH, we take pride in a culture built on collaboration, innovation, and uncompromising integrity. We are looking for individuals who share these values and are committed to customer-centricity and ethical excellence. All employees are expected to uphold our Code of Conduct, which serves as a guiding framework for responsible behavior across everything we do — from how we work with each other to how we engage with clients and partners globally.

Posted 5 days ago

Soho, London Hybrid working: 3 days in the office Tues - Thurs The Role We are looking for a brilliant and motivated Junior Data Scientist to join our Marketing Analytics team. In this role, you will help us measure, optimize, and supercharge our marketing investments across our core brands, with a strong focus on our mathematical and econometric modelling frameworks. You will have a unique opportunity to develop a dual profile: a rigorous data scientist who can manipulate complex datasets and build advanced models, and a strategic partner who translates those insights into clear growth strategies. You will step into a key position, taking hands-on ownership of our Marketing Mix Modelling (MMM) pipeline and helping us bridge the gap between statistical modelling, incrementality testing, and real-world multi-million-pound budget decisions. At LiveScore Group, we’re the proud home of three of the most exciting brands in the sports and gaming world: LiveScore, LiveScore Bet and Virgin Bet. A fully owned and operated ecosystem that converges the two worlds of sports media and sports betting. We’re proud of the high ratings for our commitment to excellence and fueling fan’s passion for sport driving us to the top. We don’t just lead; we innovate. Our cutting-edge products and immersive experiences set the standard, but it’s our people who truly make the difference. Every day, our team embody our values: adaptability, teamwork, a fan-driven approach, and an ever-curious mindset that fuels our ambition. As we scale and continue to create a culture that allows all employees to thrive, we know we need the most talented people with diverse backgrounds, perspectives and skills. If you’re good at what you do, come and join us. The more inclusive we are, the more amazing experiences we can create for our users. We know that job descriptions can sometimes seem daunting and you might not feel you tick every box. But, if you’re passionate about the role and have relevant experience, we want to hear from you! Key Responsibilities Hands-on Marketing Mix Modelling (MMM): Play a key role in our end-to-end MMM pipeline. You will be responsible for gathering, cleaning, and structuring time-series marketing data (spend, impressions, external factors) and building/refining statistical models to measure the ROI of our channels. Model Calibration Triangulation: Help calibrate our MMM outputs using results from incrementality testing. You will actively use ground-truth experimental data (e.g., GeoX tests, attribution model). Budget Scenario Planning: Translate model outputs into actionable simulation tools and optimization scenarios. You will help stakeholders answer critical "what-if" questions regarding budget reallocations and product splits. User Data Performance Analytics: Use SQL to deep-dive into first-party user data and tracking key KPIs. Data Quality Pipeline Ownership: Collaborate with our Data Engineering teams to automate data ingestion pipelines, ensuring high-quality, model-ready inputs from ad-platforms, attribution tools, and internal databases. Stakeholder Communication: Translate complex econometric, Bayesian, or machine learning concepts into clear, commercial, and highly visual recommendations for marketing team leads and senior leadership. Skills, Knowledge and Experience Proven experience or a degree in a highly quantitative field (e.g., Econometrics, Statistics, Mathematics, Data Science, Economics, or Engineering). Python (or R) proficiency: Solid programming foundations for data manipulation (pandas, numpy), statistical modeling, and machine learning (we primarily use Python). Strong SQL skills: Comfortable writing efficient, structured queries to extract and aggregate massive datasets from relational databases. MMM Frameworks (Desirable): Exposure to or strong interest in modern open-source MMM libraries (e.g., Meta's Robyn, Google's Meridian, or PyMC/Bayesian workflows). Solid foundation in econometrics, time-series analysis, and regression modeling (OLS, Ridge/Lasso, Bayesian regression). Good understanding of testing and experimentation methodologies (A/B testing, GeoX testing, hypothesis testing, and statistics like MDE and bias analysis). A keen interest in marketing dynamics (customer acquisition, CAC, CPA, ROI, and media attribution). We welcome applications from recent graduates and early career professionals, including candidates who have gained initial experience in an agency or client side environment, ideally with exposure to Marketing Mix Modelling (MMM), marketing effectiveness, or related marketing analytics. What can we offer? Company Performance Bonus Flexible Working Agreements where applicable Private Healthcare Scheme + Employee Enhanced Assistance Enhanced Family Leave - Maternity, Shared Parental Adoption Leave: up to 6 months at full pay and 6 months at half pay. Paternity leave: up to 4 weeks at full pay Subsidised Gym Membership Annual Travel Card Loan Ride to Work Scheme Life Assurance (x3 salary) Contributory Pension Plan Virgin Family: Giving you access to exclusive Virgin offers and experiences Thursday drinks in the office and regular socials

Posted 1 week ago

We are looking for our future Junior Data Scientist to join our team in Jakarta or Kuala Lumpur and kick-start an exciting journey in Data AI, working on high-impact projects for local and international clients. Who Are We? Artefact is a new-generation consulting firm fully dedicated to Data and AI transformation . With more than 2,000 talents across 24 countries , we help organizations unlock the full potential of their data to accelerate business performance. Our mission? To transform data into measurable business impact. We work across the entire data value chain, including: Automating critical business processes through AI Optimizing and personalizing customer experiences Data strategy digital marketing Media activation, measurement advanced analytics Building and deploying robust and scalable data solutions Our expertise is trusted by more than 1,000 clients worldwide , including AccorHotels, Orange, Carrefour, Engie, Emirates, Deutsche Telekom, Monoprix, and many more. To support our continued growth in Southeast Asia, our Jakarta and Kuala Lumpur offices are looking for curious and motivated Junior Data Scientists who are eager to learn, grow, and develop alongside an experienced team. Our Mission At Artefact, our mission is to help organizations become AI champions by unlocking the full value of their data . We believe in a unique approach that combines business expertise, cutting-edge technology, and responsible AI practices . We strive to create an environment where continuous learning, initiative, collaboration, and knowledge sharing drive our collective success. Your Role As a Junior Data Scientist , you will join a supportive yet challenging environment where experienced team members will help you develop your technical and consulting capabilities. Your responsibilities will include: Collecting, cleaning, and preparing datasets required for analytical and Data Science projects. Conducting exploratory data analysis and developing visualizations to identify trends, patterns, and insights. Implementing and testing Machine Learning models under the guidance of Senior Data Scientists. Supporting feature engineering and variable selection in collaboration with the wider project team. Preparing concise reports and presentations to communicate findings and results to internal teams and clients. Properly documenting scripts, models, methodologies, and data pipelines. Keeping up to date with emerging Data Science methodologies, technologies, and tools. Collaborating with Data Scientists, Data Engineers, Analysts, and Consultants to deliver data-driven solutions that create measurable business impact. To show that you have read this job posting carefully, please include the word "curiosity" in your application. What We Are Looking For Bachelor's or Master's degree in Data Science, Mathematics, Statistics, Computer Science, Engineering , or another relevant quantitative field. Final-year students may also be considered. 1–2 years of experience in Data Science . Relevant internships, academic projects, research, or practical Data Science experience will also be considered. Solid foundation in Python , including libraries such as pandas, NumPy, scikit-learn, and matplotlib. Understanding of fundamental Machine Learning algorithms, including regression, classification, and clustering . Basic understanding of descriptive and inferential statistics. Intermediate SQL skills, including queries, joins, and aggregations. Familiarity with Git and notebook environments such as Jupyter or Google Colab. Strong analytical and problem-solving skills. Curiosity, attention to detail, and a genuine desire to learn and grow in a challenging environment. Good communication skills and the ability to collaborate effectively within multidisciplinary teams. Comfortable working in an international and fast-paced consulting environment. Why Join Us? Joining Artefact in Jakarta or Kuala Lumpur means much more than just starting a new job. You will have the opportunity to: Kick-start and accelerate your career at a fast-growing global Data AI consulting company . Learn directly from and be mentored by experienced Data Science and AI professionals. Work on real-world, high-impact Data AI projects. Gain exposure to a wide variety of industries, business challenges, and technologies. Grow quickly in an international, agile, and intellectually stimulating environment. Collaborate with colleagues and experts across Artefact's global network. Create tangible business impact for clients across industries such as financial services, telecommunications, retail, consumer goods, technology, and energy . What We Offer A full-time position based in Jakarta, Indonesia or Kuala Lumpur, Malaysia . Opportunities to work on high-impact projects for leading local, regional, and international clients. Access to Artefact's learning and development ecosystem, including MOOCs, internal knowledge-sharing sessions, technical training, certifications, and mentoring. Exposure to a global network of Data, AI, and consulting professionals. A collaborative, entrepreneurial, and fast-growing working environment. Opportunities for accelerated career development based on performance and capabilities. Our Recruitment Process 1. Initial HR Discussion A phone or video conversation to learn more about your background, experience, projects, and motivations, while giving you the opportunity to learn more about Artefact and the role. 2. Technical Challenge A practical Data Science exercise designed to understand how you approach data, solve problems, and structure your analysis. 3. Manager Interview Meet the Team You will meet your potential manager and members of the team to discuss your technical experience, problem-solving approach, and how you could contribute to Artefact. 4. Offer If everything goes well, we will proceed with an employment offer. 📩 Ready to join the adventure? Click Apply and start your journey with Artefact! P.S. We hire people, not just profiles. Be yourself and show us what makes you unique!

Posted 1 week ago

CESAR is seeking a Junior Data Scientist with a strong interest in Generative AI and related technologies. The ideal candidate will develop AI-based solutions, implement architectures utilizing Retrieval-Augmented Generation, and collaborate in multidisciplinary teams. Applicants should have a degree in Computer Science or related fields, and experience in AI and Machine Learning is essential. CESAR offers a flexible work environment and a variety of employee benefits aimed at fostering inclusivity and professional growth.

Posted 3 weeks ago

This is a fully remote opportunity with hybrid available to those local to Boston. Gradient AI: Gradient AI is the decision-intelligence partner for the insurance industry, giving customers an advantage in how they make decisions by revealing risk others miss and translating it into stronger performance and real-world impact. Our platform harnesses a vast industry data lake – tens of millions of policies and claims enriched with economic, health, geographic, and demographic signals – integrating cleanly with existing workflows to make complex risk clear, usable, and actionable. Our customers include carriers, brokers, consultants, and specialized insurance organizations across the industry . We are b acked by $56M in Series C funding and scaling fast – and it's an exciting time to join the team ! About the Role: We are looking for a Principal Data Scientist with deep, specialized expertise to lead our organization's most complex and high-impact modelling and analytical initiatives. As a recognized technical authority, you will set modelling strategy across the organization, drive our most novel work, and raise the technical standard for how we build and ship models. How you will make an impact: Leverage the best of modern deep learning large language models with traditional data science techniques to create powerful hybrid models with real uplift. Brainstorm, prototype, prove, deploy, and realize the value of your work in market quickly. Everything you would expect on a world-class data science team solving world-class problems. Big data. Federated learning. Unstructured data challenges. Timeseries and sequence modelling. A self-serve buffet of techniques from GLMs to XGBoost to Transformers. Tell stories with your data. Inspire trust in customers, stakeholders, and prospects by turning murky math into a powerful message that drives the bottom line. Who you are and why we want to work with you: You like getting things over the line. You have an insatiable desire to deliver value now and improve next. MVP perfection is achieved not when there is nothing more to add, but when there is nothing left to take away. You are not a software engineer, but you give them a run for their money. You prefer Python to R and don’t understand why there is still a debate. Jupyter is a necessary evil, and you’ve never met a command line that scared you away. You still do a better job than Claude, and you’re skeptical of your friends who say they never code any more. You love to take initiative and spearhead new projects, even if they are not well defined. You build systems bigger than you. You contribute to open source, build packages your peers want to use, or design frameworks to elevate your team. Reuse is a strategy, not a buzzword. Skills needed to succeed: Bachelor's degree in Computer Science, Data Science, Biostatistics, Mathematics, or similar related field AND 8+ years of professional data science experience building predictive models OR Master’s or Ph.D in Computer Science, Data Science, Biostatistics, Mathematics, or similar related field AND 5+ years of professional data science experience building predictive models Expert-level knowledge of deep learning and ML algorithms and the core Python data science ecosystem. Strong communication and collaboration skills, particularly communicating with nontechnical stakeholders and leadership, and helping to pivot technical roadmaps to deliver their intended value rapidly Deep experience with natural language, medical data, long-tail predictions, or similar related problem spaces Strong familiarity with all phases of the MLOps model lifecycle, with experience creating team standards and practices to enforce quality and speed Deep experience being accountable for model impact long term – from MLOps pipelines to monitor for drift, to KPI and impact monitoring, driving incremental and long-term improvements, triaging issues, addressing tech debt responsibly, etc. Bonus Qualifications: Fluency with actuarial methods and working with actuaries is a plus Familiarity with healthcare and medical data Familiarity with underwriting and claims, or predicting long-tailed and/or rare events What We Offer: A fun, team-oriented startup culture. Generous stock options - we all get to own a piece of what we’re building. Unlimited vacation days. Flexible schedule that supports working from home. Full benefits package includes medical, dental, vision, 401k, paid paternal leave, and more. Ample opportunities to learn and take on new responsibilities. We are an equal opportunity employer. Salary Range: $190,000-235,000k base salary annually. This role is also eligible for an annual performance bonus, equity grant, and a comprehensive benefits package. In accordance with the Massachusetts Pay Transparency Law, we are providing a good-faith salary range for this position at the time of posting. The actual salary offered will depend on the level at which the candidate is hired, as well as their experience, skills, qualifications, and location. Compensation may grow over time through merit-based increases, promotions, and company-wide adjustments. If your salary expectations fall outside this range, we still encourage you to apply so we can have a conversation.

Posted 1 week ago

Blink Health is seeking a Principal Data Scientist to join their elite team focused on enhancing healthcare commerce through data. This role demands deep expertise in data science, enabling the development of innovative algorithms and models to enhance patient care. The ideal candidate will translate complex data findings into actionable insights, collaborating closely with various teams to improve product strategy and customer experience. With a commitment to innovation, the position offers an opportunity to significantly impact the healthcare landscape while working within a rapidly growing organization.

Posted 2 weeks ago

AbbVie is seeking a Principal Data Scientist to lead advanced analytics initiatives that optimize commercial engagement and performance within the pharmaceutical sector. The successful candidate will drive technical strategy, model design, and AI/ML solution development while collaborating with cross-functional teams. This role emphasizes technical expertise in machine learning and statistical modeling, requiring a minimum of 8 years of relevant experience. Join a diverse and innovative team focused on impactful health solutions, where creativity and collaboration are at the forefront of success.

Posted 2 weeks ago

On is seeking a Principal Data Scientist to lead data-driven projects and initiatives. The ideal candidate will have a strong background in data analysis, machine learning, and statistical modeling. This role is pivotal in enhancing decision-making processes and improving operational efficiency through data insights.

Posted 2 weeks ago