276 to 300 of 501 Apache Spark Jobs in the UK

data at scale/data pipelines, with any experience of bioinformatics/genome data advantageous. Experience of data processing platforms such as Kafka and Spark would also be useful Strong experience with Python, with any additional skills with R and/or C++ of benefit Experience of building a More ❯

data at scale/data pipelines, with any experience of bioinformatics/genome data advantageous. Experience of data processing platforms such as Kafka and Spark would also be useful Strong experience with Python, with any additional skills with R and/or C++ of benefit Experience of building a More ❯

SQL-based feature engineering to model development in Python and cloud deployment (AWS) Prototype and test new ideas that solve real business problems or spark client innovation Take ownership of workstreams within larger projects, with opportunities to lead as you grow Work across the stack — from APIs and infrastructure More ❯

SQL-based feature engineering to model development in Python and cloud deployment (AWS) Prototype and test new ideas that solve real business problems or spark client innovation Take ownership of workstreams within larger projects, with opportunities to lead as you grow Work across the stack — from APIs and infrastructure More ❯

QUALIFICATIONS Experience in building and launching deep learning and machine learning models for business applications Solid knowledge of big data and cloud technologies (e.g., Spark, AWS, etc.) Experience with information retrieval, recommender systems, natural language processing, and/or personalization algorithms Publications at top Web, Machine Learning, Natural Language More ❯

data science techniques , including regression, classification, and machine learning. Experience with deep learning or generative AI is a plus but not essential. Proficiency in (Spark)SQL and Python . Experience with PySpark is beneficial but not required. Experience designing and implementing robust testing frameworks . Strong analytical skills with More ❯

data science techniques , including regression, classification, and machine learning. Experience with deep learning or generative AI is a plus but not essential. Proficiency in (Spark)SQL and Python . Experience with PySpark is beneficial but not required. Experience designing and implementing robust testing frameworks . Strong analytical skills with More ❯

data science techniques , including regression, classification, and machine learning. Experience with deep learning or generative AI is a plus but not essential. Proficiency in (Spark)SQL and Python . Experience with PySpark is beneficial but not required. Experience designing and implementing robust testing frameworks . Strong analytical skills with More ❯

data science techniques , including regression, classification, and machine learning. Experience with deep learning or generative AI is a plus but not essential. Proficiency in (Spark)SQL and Python . Experience with PySpark is beneficial but not required. Experience designing and implementing robust testing frameworks . Strong analytical skills with More ❯

data science techniques , including regression, classification, and machine learning. Experience with deep learning or generative AI is a plus but not essential. Proficiency in (Spark)SQL and Python . Experience with PySpark is beneficial but not required. Experience designing and implementing robust testing frameworks . Strong analytical skills with More ❯

s degree/PhD in Computer Science, Machine Learning, Applied Statistics, Physics, Engineering or related field Strong mathematical and statistical skills Experience with Python, Spark, and SQL Experience implementing and validating a range of machine learning and optimization techniques Effective scientific communication for varied audiences Autonomy and ownership of More ❯

Functional Relevance of Work Experience: 15+ years of experience as an Enterprise Architect. 5+ years of industry exposure to the Government Sector. Certification across Spark and TOGAF. Other Desired Skills: Skilled in generating business cases and canned presentation material that can be reused across multiple customers. Strong leadership abilities More ❯

are a plus Familiarity with version control software (git or svn) Experience with cloud computing, AWS preferred Exposure to data technologies such as Kafka, Spark or Delta Lake is useful but not mandatory. More ❯

in using Python (pandas, numpy, matplotlib, seaborn) for exploratory data analysis and data visualization. Big plus is practical familiarity with the big data stack (Spark, Presto/Athena, Hive). You have experience with BI tools (e.g., Looker, Tableau, Google Data Studio) to create compelling visual representations of data. More ❯

machine learning systems such as profiling and debugging and understanding of system performance and scalability - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. PREFERRED QUALIFICATIONS - Experience with popular deep learning frameworks such as MxNet and Tensor Flow. - PhD More ❯

data mining and statistics. Traffic quality systems process billions of ad-impressions and clicks per day, by leveraging leading open source technologies like Hadoop, Spark, Redis and Amazon's cloud services like EC2, S3, EMR, DynamoDB and RedShift. The candidate should have reasonable programming and design skills to manipulate More ❯

in building complex systems. Be proficient in programming languages such as Scala, Python, Java, or C#. Have knowledge of data management platforms (SQL, NoSQL, Spark, etc.). Be familiar with modern software tools (Git, CI/CD pipelines). Communicate complex concepts effectively to technical and non-technical audiences. More ❯

programming, ideally Python, and the ability to quickly pick up handling large data volumes with modern data processing tools, e.g. by using Hadoop/Spark/SQL. Experience with or ability to quickly learn open-source software including machine learning packages, such as Pandas, scikit-learn, along with data More ❯

S3) for security response and/or automation Experience with data science, machine learning, big data analytics, and/or streaming technologies (e.g., Kafka, Spark Streaming, Kinesis) Posted: December 10, 2024 (Updated about 1 hour ago) Amazon is committed to a diverse and inclusive workplace. Amazon is an equal More ❯

machine learning systems such as profiling and debugging and understanding of system performance and scalability Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. PREFERRED QUALIFICATIONS Experience with popular deep learning frameworks such as MxNet and Tensor Flow. PhD Amazon is an More ❯

tools. We use Terraform, Ansible, k8s and Datadog to manage a range of RHEL/Rocky 9 hosts. Our analytics clusters make use of Spark, HBASE and HDFS. Experience in designing and implementing scalable infrastructure solutions, ideally with some exposure to parallel processing environments used for large-scale analytics. More ❯

Statistics, CS, Machine Learning, Operations Research or in a highly quantitative field. Knowledge of distributed computing and experience with advanced machine learning libraries like Spark MLLib, Tensorflow, MxNet, etc. Strong publication record in international conferences on machine learning and artificial intelligence. Amazon is committed to a diverse and inclusive More ❯

In terms of skills we're looking for a candidate with one or more of: Python A flare for visualisations NLP Big data architectures Spark ML Knowledge of novel DNN architectures GANs ML Vision About Kortical Just as every company is now a tech company, they will also have More ❯

or Development, Content Distribution/CDN, Scripting/Automation, Database Architecture, Cloud Architecture, Cloud Migrations, IP Networking, IT Security, Big Data/Hadoop/Spark, Operations Management, Service Oriented Architecture etc. Experience in a 24x7 operational services or support environment. Experience with AWS Cloud services and/or other More ❯

solutions such as Openstack, MicroCloud and Ceph, and solutions that could be deployed either on-premises or in public clouds such as Kubernetes, Kubeflow, Spark, PostgreSQL, etc. The team works hands-on with the technologies by deploying, testing and handing over the solution to our support or managed services More ❯