251 to 275 of 472 Apache Spark Jobs in England

data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive More ❯

experience deploying ML models into production environments, including both batch and real-time/streaming contexts Proficiency working with distributed computing frameworks such as Apache Spark , Dask, or similar Experience with cloud-native ML deployment , particularly on AWS , using services like ECS, EKS, Fargate, Lambda, S3, and more More ❯

create sustainable and resilient solutions. Your experience: Bachelor's degree in Computer Science or relevant certification. Expert level experience in Java and preferably in Spark and Python. Well versed in Cloud architecture and have delivered to one or more; Azure (preferred). Demonstrate hands-on engineering in large scale More ❯

and RDBMS. Eligible for SC clearance (public sector experience is a strong plus). Nice-to-Have: Experience with big data tools (e.g. Hadoop, Spark, MapReduce). Exposure to microservices for data delivery and streaming architectures. AWS certifications (e.g. Solutions Architect, Big Data). Knowledge of data visualization tools More ❯

MMM. Expertise in regression modeling, statistical and ML techniques . Experience with probabilistic programming, Bayesian methods, and MCMC. Proficient in SQL and/or Spark for large-scale data mining. Solid understanding of statistical foundations and mathematical modelling. Familiarity with cloud-based frameworks; Azure preferred. Advanced degree (MS/ More ❯

MMM. Expertise in regression modeling, statistical and ML techniques . Experience with probabilistic programming, Bayesian methods, and MCMC. Proficient in SQL and/or Spark for large-scale data mining. Solid understanding of statistical foundations and mathematical modelling. Familiarity with cloud-based frameworks; Azure preferred. Advanced degree (MS/ 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 ❯

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 ❯

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 ❯

Python or related language - Experience with neural deep learning methods and machine learning PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - PhD Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does 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 ❯