Data Scientist Data Engineer Jobs

Data Scientist / Data Engineer

From $202/yr

About Nucs AI Nucs AI is revolutionizing cancer care through cutting-edge AI and medical imaging technology. Founded in 2024 by a multidisciplinary team of oncologists, AI researchers, and healthcare innovators, we’re tackling one of medicine’s most pressing challenges: the growing demand for accurate, timely cancer diagnostics in the face of rising scan volumes and limited radiologist capacity. We sit at the intersection of diagnostics and treatment planning - building AI-powered tools at the convergence of medical imaging, radioligand therapy, and artificial intelligence. Starting with prostate cancer and expanding across oncology, we partner with world-leading medical institutions and pharmaceutical companies across the US, Europe, and Australia to bring precision oncology into everyday clinical practice. Our mission is to enhance diagnostic precision and expand access to expert-level cancer care, improving patient outcomes worldwide. We’re venture-backed, early-stage, and building a team that blends deep clinical expertise with engineering intensity - moving with the rigor the medical field demands and the speed the problem deserves. What you'll do Build auditable data pipelines for large clinical, diagnostic, and medical imaging datasets in the cloud. Own statistical analysis across clinical studies, diagnostic performance, model evaluation, and data quality. Apply classical machine learning and deep learning methods to data analysis problems. Automated ontology induction from medical documents using large language models. Build dashboards and data observability tooling. Maintain strong data lineage, provenance, traceability, and reproducibility across data workflows. Produce analyses and supporting evidence that hold up in regulatory submissions and audits. What we're looking for A master's degree or PhD in computer science, data science, engineering, mathematics, statistics, physics, economics or a related discipline 3+ years of hands-on experience in data engineering or a closely related field, with demonstrated development of production-grade data solutions Proficiency in SQL and Python and software-development standards such as Git-based workflows, automated testing, code reviews and CI/CD Comfort working with medical imaging formats including DICOM and NIfTI. Practical experience with classical machine learning and explainable ML. Working fluency with deep learning and modern LLM tooling. Experience with cloud data infrastructure. We use GCP, but equivalent platforms are fine. A strong working understanding of data lineage, provenance, traceability, and reproducibility. Unusual attention to detail around data completeness, validity, consistency, and edge cases. Flexibility at adapting to new technologies Awareness of good software practices Strongly preferred Experience with medical imaging -clinical trials, pharmaceutical, healthcare or another regulated industry is an advantage Experience with knowledge graphs / temporal knowledge graphs Experience producing statistical analyses or technical evidence used in a regulatory submission. Experience with model interpretability techniques such as SHAP. Why Nucs AI Mission with real impact – Your work directly improves how cancer patients are diagnosed and treated. Ground-floor opportunity – Early-stage company, meaningful equity, and outsized influence on the direction we take. World-class collaborators – Work alongside leading oncologists, nuclear medicine physicians, and AI researchers globally. Massive market tailwinds – Radioligand therapy and AI-driven oncology are multi-billion dollar growth markets. Autonomy and flexibility – Remote-first, flexible working. We hire great people and trust them to deliver. Equity upside – Competitive equity package. We’re building something big and want you to share in it. How to Apply Submit your resume and a brief note on why this role and Nucs AI excite you. Equal Opportunity Nucs AI is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all team members. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status. Find Jobs in Germany on Arbeitnow

Data Scientist and Pipeline Engineer

From $99,000/yr

Job Number: R0250572 Data Scientist and Pipeline Engineer The Opportunity: As a data scientist, you’re excited at the prospect of unlocking the secrets held by a data set, and you’re fascinated by the possibilities presented by IoT, machine learning (ML), and artificial intelligence (AI). In an increasingly connected world, massive amounts of structured and unstructured data open new opportunities. As a data scientist at Booz Allen, you can help turn these complex data sets into useful information to solve global challenges. Across private and public sectors, from fraud detection to cancer research, to national intelligence, we need you to help find the answers in the data. On our team, you’ll use your leadership skills and data science expertise to create real-world impact. You’ll work closely with clients to understand their questions and needs and then dig into their data-rich environments to find the pieces of their information puzzle. You’ll guide teammates and lead the development of algorithms and systems. You’ll use the right combination of tools and frameworks to turn sets of disparate data points into objective answers to advise your clients as they make informed decisions. Ultimately, you’ll provide a deep understanding of the data, what it all means, and how it can be used. Work with us as we use data science for good. Join us. The world can’t wait. You Have: * 3+ years of experience with statistical and general-purpose programming languages for data analysis * 3+ years of experience analyzing structured and unstructured data sources * Experience with data exploration, data cleaning, data analysis, data visualization, or data mining * Experience developing predictive data models, quantitative analyses, and visualization of targeted data sources * Experience with natural language processing, text mining, or ML techniques * Experience with REST APIs, webhooks, and automation middleware * Experience integrating enterprise systems such as Jira, Confluence, APIs, or in-house platforms * Experience with pipeline hardening, including model lineage tracking, automated validation, monitoring drift, data integrity or pipeline health * TS/SCI clearance * Bachelor’s degree Nice If You Have: * Experience in the development of algorithms leveraging CDS, GitLab, CI/CD, Argo CD, R, Python, or SQL and NoSQL * Experience with distributed data and computing tools, including MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL * Experience with visualization packages, including Palantir, Plotly, Seaborn, or ggplot2 * Master's degree Clearance: Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance is required. Compensation At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen’s benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page. Salary at Booz Allen is determined by various factors, including but not limited to location, the individual’s particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $99,000.00 to $225,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen’s total compensation package for employees. This posting will close within 90 days from the Posting Date. Identity Statement As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud. Candidate AI Usage Policy AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided . Work Model Our people-first culture prioritizes the benefits of collaboration. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings. * Remote: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility. * Hybrid: If this position is listed as hybrid, you will be expected to work from a Booz Allen or customer facility, in alignment with your leadership's expectations and the needs of the role. * Onsite: If this position is listed as onsite, work will primarily be performed full-time at a customer facility, where employees will collaborate directly with colleagues and customers as required by the role. Commitment to Non-Discrimination All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.

Data Scientist, Network Fabric Engineering

From $104/yr

Description AWS Networking operates one of the largest and most complex networks on the planet. The team you'd join is responsible for the availability of that network — measuring how it performs for customers, predicting where it is most likely to degrade, and reshaping how we operate it as the workload grows. We are in the middle of a significant change in how network operations are run. Lessons from our recent work on automation, AI, and ML — including agentic systems that triage and mitigate incidents alongside engineers — are feeding into a broader rethink of where humans focus, where automation takes over, and how we measure whether either is working. We are looking for a Data Scientist to join the team in Sydney to drive the data science strategy behind that change. You will define the metrics that matter, own the evidence the team uses to make decisions, and measure whether each decision delivered the outcomes we expected. You'll be the data science voice on a team of senior network and software engineers — the person who decides what we measure, how we measure it, and what the numbers actually mean. Concretely, that means setting the analytical bar for the program, designing risk and reliability models against telemetry from millions of network devices, surfacing the patterns that drive customer-impact incidents, and turning that analysis into the dashboards and metrics our leaders use to set priorities. It also means owning the evaluations that tell us when a new piece of automation — including the agents we are rolling out to support engineers on the front line — is actually moving the needle on availability, and not just adding noise. If you are a scientist who wants to shape how a tier-one production network is run — using data to drive program strategy, not just to support it — at a scale no academic lab or startup can match, and you're at your best as the data science voice embedded in a team of engineers, this is the team for you. Key job responsibilities * Define and drive the data science strategy for the program — the metrics, the experiments, and what counts as evidence that a change worked * Lead the design and deployment of predictive risk and reliability models for network availability, using device failures, alarm telemetry, ticket data, and traffic signals * Own the evidence behind program decisions: where availability is at risk, where automation is ready to expand, where engineering effort has the highest leverage. Defend recommendations to senior technical and business audiences * Design and own the operational analytics and dashboards (Amazon QuickSight, Amazon CloudWatch, Python) used by senior leadership to track network health and the impact of operational change * Design and run experiments to evaluate the automation we are rolling out — including agentic systems supporting engineers on incidents — measuring whether each rollout improved availability * Drive data quality and classification improvements — event categorisation, root-cause attribution — so the program's metrics rest on solid ground * Build and own event-driven scoring pipelines (Python, SQL, AWS Lambda, Amazon S3, Amazon Athena) that keep the decide / measure / improve loop running * Bring statistical rigour to the engineers you partner with — review experiment designs, push back on unsupported assumptions, and raise the bar on how the team uses evidence A day in the life You might start the morning defining how the team will measure a new initiative — the success metrics, the counterfactual, the bar for calling it a win. By mid-morning you're with the engineering team turning a proposal into a decision: walking through trade-offs, pushing back where the data doesn't support an assumption. The afternoon is outcome measurement — refining the evaluation pipeline that tracks last week's rollout, updating the CloudWatch dashboard senior leadership uses to gate the next expansion, and prepping the data for an upcoming Director review. About The Team We sit inside AWS Networking with a strong Sydney presence and a remit that spans network availability, the data and analytics that support it, and the automation we are building to change how operations are done. You'd be the data science voice in a small, senior team of network and software engineers in Sydney, partnering with the broader network engineering organisation across Seattle and Dublin. Small team, high autonomy, direct line to senior leadership, and a roadmap with real production impact rather than research demos. Basic Qualifications * 2+ years of data scientist experience * 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience * 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience * 1+ years of working with or evaluating AI systems experience Preferred Qualifications * Bachelor's degree or above in Science, Technology, Engineering, or Mathematics (STEM) * Knowledge of machine learning concepts and their application to reasoning and problem-solving * Experience in Python, Perl, or another scripting language * Experience in a ML or data scientist role with a large technology company * Experience in defining and creating benchmarks for assessing GenAI model performance Acknowledgement Of Country In the spirit of reconciliation Amazon acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today. IDE Statement Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Company - Amazon Support Services Pty Ltd Job ID: A10460021

Data Scientist/Engineers x5 - DV Clearance Required

Role Overview Kaze Consulting is growing, driven by rising demand from clients who want to move beyond the promise of AI and apply it to solve complex, real-world problems that matter. We are looking for 5x technically strong Data Scientists/Engineers to join our Data \& AI team, working on complex data-driven problems within secure government environments. This role combines data science, software engineering and data engineering. You will work across the full data science lifecycle: understanding operational and business problems, defining data requirements, exploring and preparing large datasets, developing analytical and machine-learning solutions, evaluating performance, and taking successful proofs of concept through to production. The role suits someone with a strong technical foundation in Computer Science, Physics or a related quantitative discipline, who is comfortable working directly with large-scale data platforms. Key Responsibilities • Work with stakeholders to translate complex business and operational problems into clear analytical and data science requirements. • Contribute across the full data science lifecycle, from discovery, data requirements and collection through understanding, preparation, modelling, evaluation, deployment and feedback. • Develop proofs of concept and progress successful approaches into robust, production-ready solutions. • Work with large and complex datasets hosted within Hadoop and/or Stackable-based data platforms. • Build scalable processing and analytical workflows using Python, SQL, Spark and PySpark; query distributed datasets using Trino and Hive. • Develop and maintain Jupyter and Python data science environments, alongside scheduled analytical and processing workloads, including orchestration of Trino queries. • Perform data exploration, feature engineering, statistical analysis and machine-learning model development where appropriate. • Apply strong engineering practices, including modular development, testing, version control, reproducibility and maintainability. • Work with engineers, architects, analysts and operational stakeholders to integrate analytical capabilities into wider platforms. • Evaluate solutions against technical and operational requirements; use feedback to improve them iteratively. • Contribute to technical documentation, architecture decisions and knowledge sharing. • Work within Agile/Scrum teams, contributing to planning, refinement, reviews and retrospectives. • Deliver in accordance with the security, governance and assurance requirements of UK Government and Defence environments Must Haves: * Be based in the UK and willing to travel onsite 2-3 days per week * Hold a British passport * Currently hold a valid DV clearance If you’re motivated by challenging work, inspired by the potential of AI, and want to be part of a team shaping how it is applied in the real world, we’d like to hear from you at hello@kaze-consulting.com