Principal Data Scientist

Senior Data Scientist 2

Senior Business Intelligence Analyst

Manager, Data Science (GNS)

Senior Data Scientist II

Senior Data Scientist

Responsibilities: <ul><li>Design, build, and optimise agentic systems capable of breaking down complex tasks into executable steps.&nbsp;</li><li>Innovate in context engineering strategies (retrieval-augmented generation, dynamic context construction, memory management) to maximise LLM effectiveness.&nbsp;</li><li>Select, fine-tune, and adapt large language models (LLMs) to align with agent objectives.&nbsp;</li><li>Enhance and extend evaluation frameworks for online and offline performance, efficiency, and success rates.&nbsp;</li><li>Select, benchmark, and host LLMs on Amazon SageMaker or EKS, comparing and optimising models to ensure agentic systems are fast, accurate, and cost-effective.&nbsp;</li><li>Own and prioritise a backlog of improvements to core intelligence, applying methods such as RLHF and self-learning agents.&nbsp;</li><li>Collaborate with AI engineering and product teams to deliver production-ready solutions.&nbsp;</li><li>Mentor and supervise junior data scientists and foster a culture of innovation, collaboration, and continuous improvement.&nbsp;</li></ul> Requirements: <ul><li>PhD in AI, Computer Science, Mathematics or a related field; or Master’s with equivalent experience.&nbsp;</li><li>Hands-on experience in LLMs or applied AI research in a commercial environment.&nbsp;</li><li>Proven expertise in context engineering, LLM fine-tuning, and evaluation of non-deterministic systems.&nbsp;&nbsp;</li><li>Strong programming skills in Python and proficiency in deep learning frameworks (e.g., PyTorch)&nbsp;</li><li>Strong problem-solving, analytical, and communication skills.&nbsp;</li><li>Demonstrated ability to work collaboratively with engineering and product stakeholders in an agile environment.&nbsp;</li></ul>

Responsibilities: <ul><li>Lead the design and development of LLM-powered solutions for clinical summarization, intelligent chat, and document understanding to improve patient care outcomes.</li><li>Architect and implement end-to-end machine learning pipelines, including Retrieval-Augmented Generation (RAG) systems using vector databases such as Pinecone and Weaviate.</li><li>Fine-tune and optimize state-of-the-art language models (e.g., GPT, LLaMA, Mistral) and apply advanced prompt engineering to address specialty-specific healthcare use cases.</li><li>Own project delivery end to end, collaborating with stakeholders to ensure AI solutions are ethical, scalable, reliable, and well-governed.</li><li>Mentor and support junior data scientists, fostering a culture of experimentation, learning, and innovation.</li></ul> Requirements: <ul><li>Experience: 8–12 years in Data Science/ML, with at least 3+ years specifically focused on LLMs and Generative AI.&nbsp;</li><li>Technical Mastery: Deep hands-on expertise in Python and frameworks like PyTorch, Hugging Face, LangChain, or LlamaIndex.&nbsp;</li><li>Cloud Fluency: Proven ability to deploy models at scale using AWS SageMaker, Azure ML, or GCP Vertex AI.&nbsp;</li><li>MLOps Mindset: Experience with MLflow, Airflow, Docker, and Kubernetes to ensure our "bold innovations" are also stable and reliable.&nbsp;</li><li>Academic Foundation: A strong grasp of statistical analysis and evaluation techniques to mitigate hallucinations and ensure clinical accuracy.&nbsp;</li></ul>

Role Description: <ul><li>The Continuous Improvement EMIA team reports to Operations Automotive EMIA.</li><li>By providing new generation digital solutions to our Operational teams across EMIA, our team creates full transparency and speed in the ongoing digital &amp; lean transformation(s), which will enable all involved functions to leverage data to develop business insights and roadmap updates based upon clearly arranged and understandable data. Due to the extended scope, focusing also on the connecting processes from Supplier(s) to Manufacturing ending at the Customer(s) (internal and external) we will function as ‘the’ differentiator for our Company.</li><li>The Data Scientist Automotive EMIA will report to the Smart Factory Leader Automotive EMIA.&nbsp;</li></ul> Responsibilities:&nbsp; <ul><li>Lead projects and work together with our Automotive EMIA Operations plants, internal (IT, , Corporate Technology, CoE, SC, ..) and external partners in the area of Smart Factory (Applications, ML, AI, DL), aligned with Operations Automotive EMIA Strategy.</li><li>Lead Smart Factory improvement projects (Enhancements) of existing applications together with internal / external supplier and customers (project management) until the level of RTD (Ready To Deploy)</li><li>·Use a combined knowledge of computer science and applications, modelling, statistics, analytics and maths to solve problems.</li><li>Identify and interpret data sources, manage large amounts of data, merge data sources together, ensure consistency of datasets, create visualizations to aid in understanding data.</li><li>Develop, Validate and Deploy (including Training and Coaching of the users) until the level of RTD (Ready To Deploy), Digital Factory Applications, ML models, contributing to waste elimination and efficiency improvements within all Operations functions (Manufacturing, Quality, SC, LOG, ….), this together with our internal and external partners.</li></ul>&nbsp;Requirements: Desired candidate &amp; Qualification <ul><li>Good understanding of a technology driven manufacturing company.</li><li>Knowledge of the core manufacturing technologies: Stamping, Plating, Assembly, Molding.</li><li>Experienced with data visualization tools like PowerBi, Tableau, ThingWorx,..</li><li>Good applied statistics skills, such as distributions, statistical testing, regression, etc.</li><li>Development experience in programming languages R, Python.</li><li>Knowledge, experience in JAVA scripting</li><li>Excellent pattern recognition and predictive modelling skills.</li><li>Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, neural networks and deep learning etc.</li><li>Experience in technologies like, Jupyter Notebooks, Numpy, Pandas, Seaborn, Scikit-learn, PyTorch and TensorFlow.</li><li>Exposure to recent developments in Deep Learning, Gen AI, Agentic AI domain.</li><li>Database skills, on-premises and cloud based.</li><li>Experience in AWS is an advantage, functional knowledge of AWS platforms such as Sagemaker, S3, and RedShift.</li><li>Excellent presentation skills in both spoken en written English.</li><li>&nbsp;Excellent and strong communicator</li><li>The ability to translate, explain and bring, complex data science topics to an easy understandable level, speeding up acceptance level in general.</li><li>Bachelor or master’s in data science</li><li>Team player with a solution focused problem-solving mentality.</li><li>Change agent with high Execution level, including training and coaching talents.</li><li>Passioned about the combination of Technology, Data, Analytics and Statistics with link to Quality, Product and Process Engineering</li><li>Inspired by and searching actively for new technologies and methods.</li></ul>

Responsibilities: <ul><li>Manage a team of data scientists and engineers to design, develop, and deploy advanced AI solutions.</li><li>Lead the development of AI and machine learning models to solve business problems.</li><li>Research, build, and deploy models based on shallow and deep machine learning.</li><li>Train robust NLP-based models on large datasets.</li><li>Collaborate with cross-functional teams to align AI solutions with business goals and customer needs.</li><li>Design APIs for disseminating data science outputs.</li><li>Oversee the scaling of production systems to meet growing demands.</li><li>Working closely with other data scientists and engineers to design, develop, and deploy AI solutions.</li><li>Analyzing large datasets to identify patterns and trends that can inform AI development.</li><li>Communicating findings and insights to stakeholders in a clear and concise manner.</li><li>Staying current with the latest AI and machine learning trends and technologies.</li><li>Mentoring junior data scientists and provide guidance on AI and machine learning best practices.</li><li>Driving best practices across our data science functions.</li><li>Setting strategy and team direction, with a clear vision for Data Science.</li><li>Working with product leaders to apply data science solutions.</li><li>Evaluating and creating new frameworks and defining methodologies and governance.</li><li>Leading small- to medium-sized teams (direct or indirect).</li><li>Setting a high-bar for model development.</li></ul> Requirements: <ul><li>Have substantial experience in a senior data scientist role.</li><li>Have experience in leading complex projects and customer relationships.</li><li>Have significant experience in managing larger Technical teams (direct or indirect).</li><li>Have experience in mentoring or training others, acting as a subject matter expert to guide colleagues.</li><li>Be a natural problem solver, able to take a lead in collaborating to resolve issues.</li><li>Have excellent communication skills and the ability to convey information clearly to senior stakeholders.</li></ul> Highly Desired Skills and Experience: <ul><li>PhD or Masters degree in Computer Science, Mathematics, Statistics, or a related field.</li><li>7-10+ years of experience in AI and machine learning.</li><li>Deep understanding of machine learning algorithms, including deep learning, gradient boosting, and random forests.</li><li>Experience working directly with large language models and Transformer based architectures including BERT, RoBERTa, T5 etc.</li><li>Working knowledge of applying recent LLMs including ChatGPT, GPT 3.5, OPT, BLOOM, etc.</li><li>Experience with reinforcement learning, prompt engineering, hallucination mitigation.</li><li>Working understanding of the business risks associated with applying LLM in a business.</li><li>Experience working with large datasets and distributed computing systems (e.g., Hadoop, Spark).</li><li>Strong coding skills in Python or another programming language.</li><li>Excellent communicator, with the ability to translate complex technical concepts to non-technical stakeholders.</li><li>Strong problem-solving skills and the ability to think outside the box. </li></ul>

About the Role : <ul><li>As a data scientist on our team, you will work on new product development in a small team environment writing production code in both run-time and build-time environments.&nbsp;</li><li>You will help propose and build data-driven solutions for high-value customer problems by discovering, extracting, and modeling knowledge from large-scale natural language datasets including matter and contract repository, invoice/legal spend data and work management.&nbsp;</li><li>You will prototype new ideas, collaborating with other data scientists as well as product designers, data engineers, front-end developers, and a team of expert legal data annotators.</li><li>You will get the experience of working in a start-up culture with the large datasets and many other resources of an established company.</li><li>We are committed to advancing gender diversity within the technology sector and supporting greater representation of women in tech. To further this commitment,</li></ul> Responsibilities: <ul><li>Develop and implement LLM-based applications tailored for legal use-cases&nbsp;</li><li>Evaluate and help maintain our data assets and training/evaluation data sets&nbsp;</li><li>Design and build pipelines for preprocessing, annotating, and managing legal document datasets&nbsp;</li><li>Collaborate with legal experts to understand requirements and ensure ML-applications meet domain-specific needs&nbsp;</li><li>Conduct experiments and evaluate model performance to drive continuous improvements&nbsp;</li><li>Fine-tune and deploy large language models to enhance their performance on legal text processing tasks&nbsp;</li><li>Interface with other technical personnel or team members to finalize requirements.&nbsp;</li><li>Work closely with other development team members to understand complex product requirements and translate them into software designs.&nbsp;</li><li>Successfully implement development processes, coding best practices, and code reviews for production environments.</li></ul> Requirements:&nbsp; <ul><li>Able to work in person 2 days per week&nbsp;</li><li>Bilingual English and Spanish&nbsp;</li><li>Practical experience with large language models, prompt engineering, fine-tuning RAG-based applications and benchmarking, using frameworks such as LangChain&nbsp;</li><li>MS in Data Science, Computer Science, Statistics, Machine Learning, or relevant work experience&nbsp;</li><li>Practical experience in Natural Language Processing methods and libraries such as spaCy, word2vec, Flair, BERT (ways to vectorize text data)&nbsp;</li><li>Formal training in machine learning: dimensionality reduction, clustering, embeddings, and sequence classification algorithms&nbsp;</li><li>Strong Python background&nbsp;</li><li>Knowledge of AWS, GCP, Azure, or other cloud platform&nbsp;</li><li>Understanding of data modeling principles and complex data models.&nbsp;</li><li>Proficiency with relational and NoSQL databases as well as vector stores (e.g., MySQL, Postgres, Solr, Elasticsearch/OpenSearch)</li><li>Knowledge of Spark-Scala, Ray or other distributed computing systems highly preferred&nbsp;</li><li>Knowledge of API development, containerization, and machine learning deployment highly preferred&nbsp;</li><li>Experience with ML Ops/AI Ops including experiment tracking tools like LangFuse and DVC&nbsp;</li><li>Experience with deep learning frameworks such as PyTorch, Tensorflow and Hugging Face Transformers Work in a way that works for you We promote a healthy work/life balance across the organization. </li><li>We offer an appealing working prospect for our people.&nbsp;</li><li>With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate. </li><li>Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.</li></ul>

Responsibilities: <ul><li>Working closely with other data scientists and engineers to design, develop, and deploy AI solutions.</li><li>Leading the development of advanced AI and machine learning models to solve complex business problems Analyzing large datasets to identify patterns and trends that can inform AI development.</li><li>Collaborating with cross-functional teams to ensure AI solutions are aligned with business goals and customer needs.</li><li>Leading the automation and lifecycle management of sophisticated data systems. Mentoring junior data scientists and provide guidance on AI and machine learning best practices.</li><li>Designing APIs for disseminating data science outputs to various business units. Overseeing the scaling of production systems to meet growing demands.</li><li>Working closely with other data scientists and engineers to design, develop, and deploy AI solutions.</li><li>Leading the development of advanced AI and machine learning models to solve complex business problems Analyzing large datasets to identify patterns and trends that can inform AI development.</li><li>Collaborating with cross-functional teams to ensure AI solutions are aligned with business goals and customer needs.</li><li>Leading the automation and lifecycle management of sophisticated data systems.</li><li>Mentoring junior data scientists and provide guidance on AI and machine learning best practices.</li><li>Designing APIs for disseminating data science outputs to various business units.</li><li>Overseeing the scaling of production systems to meet growing demands.</li></ul> Requirements: <ul><li>Possess an advanced or Masters education in Computer Science, Mathematics, Statistics, or a related field. Have experience working directly with large language models and transformer-based architectures including BERT, RoBERTa, T5 etc.</li><li>Be proficient in working with big data technologies and tools like Hadoop, Spark, or AWS.</li><li>Have experience and knowledge of applying LLMs including ChatGPT, GPT 3.5, Claude, Mistral, etc.</li><li>Be a natural problem solver, able to lead and mentor junior data scientists, and collaborate with cross-functional teams.</li><li>Demonstrate proficient experience with machine learning algorithms, including deep learning, gradient boosting, and random forests Possess advanced programming skills in Python, R, or other relevant languages for data analysis.</li></ul>

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6 bioinformatics scientist Jobs found

Principal Data Scientist

Senior Data Scientist 2

Senior Business Intelligence Analyst

Manager, Data Science (GNS)

Senior Data Scientist II

Senior Data Scientist

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6 bioinformatics scientist Jobs found

Principal Data Scientist

Senior Data Scientist 2

Senior Business Intelligence Analyst

Manager, Data Science (GNS)

Senior Data Scientist II

Senior Data Scientist

WhiteCrow WhiteCrow is on a mission to connect companies with the best talent across the globe.

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