Job Title: Senior Big Data SME (Subject Matter Expert) Location : Remote Budget : Upto 28 LPA to 30 LPA Work Hours: UK Time (1:30 PM – 10:30 PM IST) Industry : Technology / IT Experience : 10 to 15 years in Data Engineering, Big Data, or related roles About the Role We are hiring a Senior Big Data Subject Matter Expert (SME) to support and guide ongoing cloud data initiatives, with a focus on mentorship, project support, and hands-on training in modern Big Data tools and technologies. This role is ideal for someone with deep technical experience who enjoys coaching teams, troubleshooting data platform issues, and enabling engineers to grow in real-world cloud projects. You’ll collaborate with engineers, architects, and leadership to ensure best practices in cloud data solutions and smooth delivery across projects. Key Responsibilities Provide technical support and guidance across Big Data platforms in Azure, AWS, or GCP. Train and mentor engineers on Big Data tools (Spark, Kafka, Hadoop, etc.). Assist project teams with architecture design, deployment, and debugging of data pipelines. Collaborate with cross-functional teams to ensure operational excellence and platform stability. Review and improve existing cloud data pipelines, focusing on performance, cost-efficiency, and scalability. Conduct regular knowledge-sharing sessions, workshops, and best practice walkthroughs. Help define and implement data governance, access control, and security frameworks. Technical Skills Required Cloud Platforms: Azure, AWS, GCP (at least 2 preferred) Big Data Tools: Apache Spark, Kafka, Hadoop, Flink ETL Tools: DBT, Apache Airflow, AWS Glue Data Warehousing: Snowflake, BigQuery, Redshift, Synapse Containerization & Orchestration: Docker, Kubernetes (AKS, EKS, GKE) CI/CD & IaC: Terraform, GitHub Actions, Azure DevOps Security & Governance: IAM, RBAC, data encryption, lineage tracking Programming/Scripting: Python, Bash, PowerShell Preferred (Nice-to-Have) Exposure to Machine Learning pipelines and MLOps Experience with serverless computing (AWS Lambda, Azure Functions) Understanding of multi-cloud or hybrid-cloud architectures Show more Show less
Job Title: Senior Big Data SME (Subject Matter Expert) Location : Remote Budget : Upto 28 LPA to 30 LPA Work Hours: UK Time (1:30 PM – 10:30 PM IST) Industry : Technology / IT Experience : 8 to 12 years in Data Engineering, Big Data, or related roles About the Role We are hiring a Senior Big Data Subject Matter Expert (SME) to support and guide ongoing cloud data initiatives, with a focus on mentorship, project support, and hands-on training in modern Big Data tools and technologies. This role is ideal for someone with deep technical experience who enjoys coaching teams, troubleshooting data platform issues, and enabling engineers to grow in real-world cloud projects. You’ll collaborate with engineers, architects, and leadership to ensure best practices in cloud data solutions and smooth delivery across projects. Key Responsibilities Provide technical support and guidance across Big Data platforms in Azure, AWS, or GCP. Train and mentor engineers on Big Data tools (Spark, Kafka, Hadoop, etc.). Assist project teams with architecture design, deployment, and debugging of data pipelines. Collaborate with cross-functional teams to ensure operational excellence and platform stability. Review and improve existing cloud data pipelines, focusing on performance, cost-efficiency, and scalability. Conduct regular knowledge-sharing sessions, workshops, and best practice walkthroughs. Help define and implement data governance, access control, and security frameworks. Technical Skills Required Cloud Platforms: Azure, AWS, GCP (at least 2 preferred) Big Data Tools: Apache Spark, Kafka, Hadoop, Flink ETL Tools: DBT, Apache Airflow, AWS Glue Data Warehousing: Snowflake, BigQuery, Redshift, Synapse Containerization & Orchestration: Docker, Kubernetes (AKS, EKS, GKE) CI/CD & IaC: Terraform, GitHub Actions, Azure DevOps Security & Governance: IAM, RBAC, data encryption, lineage tracking Programming/Scripting: Python, Bash, PowerShell Preferred (Nice-to-Have) Exposure to Machine Learning pipelines and MLOps Experience with serverless computing (AWS Lambda, Azure Functions) Understanding of multi-cloud or hybrid-cloud architectures Show more Show less
Job Title: Senior Big Data SME (Subject Matter Expert) Location : Remote Budget : Upto 28 LPA to 30 LPA Work Hours: UK Time (1:30 PM – 10:30 PM IST) Industry : Technology / IT Experience : 8 to 12 years in Data Engineering, Big Data, or related roles About the Role We are hiring a Senior Big Data Subject Matter Expert (SME) to support and guide ongoing cloud data initiatives, with a focus on mentorship, project support, and hands-on training in modern Big Data tools and technologies. This role is ideal for someone with deep technical experience who enjoys coaching teams, troubleshooting data platform issues, and enabling engineers to grow in real-world cloud projects. You’ll collaborate with engineers, architects, and leadership to ensure best practices in cloud data solutions and smooth delivery across projects. Key Responsibilities Provide technical support and guidance across Big Data platforms in Azure, AWS, or GCP. Train and mentor engineers on Big Data tools (Spark, Kafka, Hadoop, etc.). Assist project teams with architecture design, deployment, and debugging of data pipelines. Collaborate with cross-functional teams to ensure operational excellence and platform stability. Review and improve existing cloud data pipelines, focusing on performance, cost-efficiency, and scalability. Conduct regular knowledge-sharing sessions, workshops, and best practice walkthroughs. Help define and implement data governance, access control, and security frameworks. Technical Skills Required Cloud Platforms: Azure, AWS, GCP (at least 2 preferred) Big Data Tools: Apache Spark, Kafka, Hadoop, Flink ETL Tools: DBT, Apache Airflow, AWS Glue Data Warehousing: Snowflake, BigQuery, Redshift, Synapse Containerization & Orchestration: Docker, Kubernetes (AKS, EKS, GKE) CI/CD & IaC: Terraform, GitHub Actions, Azure DevOps Security & Governance: IAM, RBAC, data encryption, lineage tracking Programming/Scripting: Python, Bash, PowerShell Preferred (Nice-to-Have) Exposure to Machine Learning pipelines and MLOps Experience with serverless computing (AWS Lambda, Azure Functions) Understanding of multi-cloud or hybrid-cloud architectures Show more Show less
Experience: 8+ years in Data Engineering or related roles, with a focus on cloud technologies and big data solutions. Technical Expertise: Deep knowledge of cloud platforms such as Azure, AWS, and GCP. Hands-on experience with Big Data technologies like Apache Spark, Hadoop, Kafka, and Flink. Solid understanding of ETL frameworks (DBT, Apache Airflow, AWS Glue, etc.). Expertise in containerization with Docker and Kubernetes (AKS, EKS, GKE). Proven experience in Data Warehousing & Modeling (Snowflake, Redshift, BigQuery, Synapse). Strong background in Data Security and Governance (IAM, RBAC, encryption, data lineage). Experience with CI/CD pipelines using Terraform, GitHub Actions, and Azure DevOps. Programming & Scripting Skills: Proficiency in Python, Bash, or PowerShell for automation tasks. Cloud Architecture: Experience designing hybrid/multi-cloud architectures to ensure high availability and fault tolerance across Azure, AWS, and GCP. Leadership & Mentorship: Proven ability to lead teams, mentor junior engineers, and collaborate effectively with cross-functional teams. Preferred Skills: Familiarity with Machine Learning pipelines and predictive analytics. Experience with Serverless Computing (AWS Lambda, Azure Functions, Google Cloud Functions).
Sr. Big Data SME Job Requirements: 8+ years of experience manipulating data sets and building statistical and machine learning models. Masters or Ph D in Statistics, Mathematics, Computer Science, or another quantitative field - Fluent English (written/spoken) Experience Developing Machine Learning / Data Science models, from coding to deployment 2+ years of experience in teaching or training. 3+ Years of Hands-on Hybrid Development experience preferred. Skills Able to train/mentor/coach in coding (mandatory python and SQL, java or C++) Project Management background preferred. Knowledge of the Consulting/Sales structure. Empathy and service attitude Fast-paced Project Management experience Desirable previous international experience (US, Canada, or Europe) Leading consultants to grow and create tangible benefits and assets. Competencies Mentor / Develop / Train consultants Orientation to results Leadership Main responsibilities of the position Collecting data through means such as analyzing business results or by setting up and managing new studies Transferring data into a new format to make it more appropriate for analysis Build tools to automate data collection Compare and analyze provided statistical information to identify patterns, relationships, and problems Define and utilize statistical methods to solve industry-specific problems in varying fields, such as economics and engineering Prepare detailed reports for management and other departments by analyzing and interpreting data Train assistants and other members of the team how to properly organize findings and read data collected Design computer code using various languages to improve and update software and applications Refer to previous instances and findings to determine the ideal method for gathering data Define and utilize statistical methods to solve industry-specific problems in varying fields, such as economics and engineering Prepare detailed reports for management and other departments by analyzing and interpreting data Train assistants and other members of the team how to properly organize findings and read data collected Design computer code using various languages to improve and update software and applications Refer to previous instances and findings to determine the ideal method for gathering data Desired Skills (Including but Not Limited to): Knowledge in Deep Learning/Neural Networks techniques, specifically NLP (Natural Language Processing, Generative AI and Computer Vision Python and SQL coding skills are indispensable Cloud experience in one of AWS - Amazon Web Service, Azure, Google Cloud Platform Proficiency oinn Machine Learning libraries and frameworks like Tensorflow, Keras, Pytorch, OpenCV, Bertl, Elmo SpaCy, NLTK, etc. Preferred- Experience creating Chatbots, and similar applications that use NLP. Object Character Recognition and Computer Vision projects like Face Recognition is a plus Experience using statistical computer languages, including Python & SQL, R is a plus to manipulate data and draw insights from large data sets Knowledge and experience in statistical and data mining techniques: GLM / Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc. Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. Ability to compile and organize statistical information retrieved and present findings to management Faculty to work toward multiple deadlines simultaneously Strong problem-solving skills with an emphasis on product development. Certification in a Cloud-Based/Machine Learning service desirable
Location : London (Relocation required - Sponsorship will be provided) Data Science SME (Subject matter expert) Experience : 12 to 18 years Job Requirements: 12 years of experience manipulating data sets and building statistical and machine learning models. Masters or Ph D in Statistics, Mathematics, Computer Science, or another quantitative field - Fluent English (written/spoken) Experience Developing Machine Learning / Data Science models, from coding to deployment 2+ years of experience in teaching or training. 3+ Years of Hands-on Hybrid Development experience preferred. Skills Able to train/mentor/coach in coding (mandatory python and SQL, java or C++) Project Management background preferred. Knowledge of the Consulting/Sales structure. Empathy and service attitude Fast-paced Project Management experience Desirable previous international experience (US, Canada, or Europe) Leading consultants to grow and create tangible benefits and assets. Competencies Mentor / Develop / Train consultants Orientation to results Leadership Main responsibilities of the position Collecting data through means such as analyzing business results or by setting up and managing new studies Transferring data into a new format to make it more appropriate for analysis Build tools to automate data collection Compare and analyze provided statistical information to identify patterns, relationships, and problems Define and utilize statistical methods to solve industry-specific problems in varying fields, such as economics and engineering Prepare detailed reports for management and other departments by analyzing and interpreting data Train assistants and other members of the team how to properly organize findings and read data collected Design computer code using various languages to improve and update software and applications Refer to previous instances and findings to determine the ideal method for gathering data Define and utilize statistical methods to solve industry-specific problems in varying fields, such as economics and engineering Prepare detailed reports for management and other departments by analyzing and interpreting data Train assistants and other members of the team how to properly organize findings and read data collected Design computer code using various languages to improve and update software and applications Refer to previous instances and findings to determine the ideal method for gathering data Desired Skills (Including but Not Limited to): Knowledge in Deep Learning/Neural Networks techniques, specifically NLP (Natural Language Processing, Generative AI and Computer Vision Python and SQL coding skills are indispensable Cloud experience in one of AWS - Amazon Web Service, Azure, Google Cloud Platform Proficiency oinn Machine Learning libraries and frameworks like Tensorflow, Keras, Pytorch, OpenCV, Bertl, Elmo SpaCy, NLTK, etc. Preferred- Experience creating Chatbots, and similar applications that use NLP. Object Character Recognition and Computer Vision projects like Face Recognition is a plus Experience using statistical computer languages, including Python & SQL, R is a plus to manipulate data and draw insights from large data sets Knowledge and experience in statistical and data mining techniques: GLM / Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc. Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. Ability to compile and organize statistical information retrieved and present findings to management Faculty to work toward multiple deadlines simultaneously Strong problem-solving skills with an emphasis on product development. Certification in a Cloud-Based/Machine Learning service desirable
🌟 Senior Data Scientist SME & AI Architect (10+ Years Experience) 🧠 We are seeking a highly accomplished and results-oriented Senior Data Scientist Subject Matter Expert (SME) with over 10 years of experience to lead our advanced analytics and AI initiatives. This is a pivotal role requiring deep technical mastery across large-scale Big Data technologies, multi-cloud environments, and cutting-edge specialized AI domains, including Generative AI, Computer Vision, and Natural Language Processing (NLP) . You will be the principal technical leader, driving strategy, setting standards, and delivering high-impact solutions that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI) , large language models ( LLMs ), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build, and optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers ( AWS, Azure, and GCP ), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models in key specialized areas: Computer Vision: Developing and optimizing models for image recognition, object detection, and video analytics. NLP: Building sophisticated systems for sentiment analysis, entity extraction, semantic search, and RAG architectures leveraging LLMs. Generative AI: Exploring and implementing cutting-edge GenAI techniques for content creation, data augmentation, and innovative product features. SME Consulting & Mentorship: Act as the internal authority and consultant, providing technical guidance, architectural review, and mentorship to junior data scientists and engineering teams. MLOps & Governance: Establish best practices for MLOps, model monitoring, version control, and model risk governance in a multi-cloud production environment. Required Skills and Expertise (10+ Years) 1. Big Data and Cloud Mastery Programming & Big Data: 10+ years of extensive, hands-on experience with Apache Spark , with strong preference for production development using Scala . Deep expertise with Apache Hive for data querying and management. Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context. 2. Advanced AI/ML Specialization Generative AI (GenAI) & LLMs: Proven experience with the architecture and implementation of Generative AI solutions, including prompt engineering, fine-tuning, and deploying Large Language Models (LLMs) . Computer Vision: In-depth knowledge of deep learning frameworks (TensorFlow, PyTorch) and experience with Computer Vision tasks (e.g., CNNs, object detection models like YOLO). NLP: Expert practical experience in NLP techniques, including transformer models, embedding generation, and building complex text-based applications. 3. Leadership & Soft Skills Technical Leadership: Proven track record of leading complex data science projects from research to production deployment. Communication: Exceptional ability to translate complex technical findings into clear, strategic recommendations for technical and executive audiences. Mentorship: Experience mentoring and training senior engineers and data scientists. Education and Certification Master’s or Ph.D. in Computer Science, Data Science, Engineering, or a highly quantitative field. Relevant professional cloud certifications (e.g., AWS Certified Machine Learning Specialty, Google Cloud Professional Data Engineer) are highly desirable.
Data Science SME (Subject matter expert) Location : London (Relocation required - Sponsorship will be provided) Experience : 12 to 18 years Job Requirements: 12 years of experience manipulating data sets and building statistical and machine learning models. Masters or Ph D in Statistics, Mathematics, Computer Science, or another quantitative field - Fluent English (written/spoken) Generative AI, Computer Vision cloud technology, NLP, Deep Learning. Experience Developing Machine Learning / Data Science models, from coding to deployment 2+ years of experience in teaching or training. 3+ Years of Hands-on Hybrid Development experience preferred. Skills Able to train/mentor/coach in coding (mandatory python and SQL, java or C++) Project Management background preferred. Knowledge of the Consulting/Sales structure. Empathy and service attitude Fast-paced Project Management experience Desirable previous international experience (US, Canada, or Europe) Leading consultants to grow and create tangible benefits and assets. Competencies Mentor / Develop / Train consultants Orientation to results Leadership Main responsibilities of the position Collecting data through means such as analyzing business results or by setting up and managing new studies Transferring data into a new format to make it more appropriate for analysis Build tools to automate data collection Compare and analyze provided statistical information to identify patterns, relationships, and problems Define and utilize statistical methods to solve industry-specific problems in varying fields, such as economics and engineering Prepare detailed reports for management and other departments by analyzing and interpreting data Train assistants and other members of the team how to properly organize findings and read data collected Design computer code using various languages to improve and update software and applications Refer to previous instances and findings to determine the ideal method for gathering data Define and utilize statistical methods to solve industry-specific problems in varying fields, such as economics and engineering Prepare detailed reports for management and other departments by analyzing and interpreting data Train assistants and other members of the team how to properly organize findings and read data collected Design computer code using various languages to improve and update software and applications Refer to previous instances and findings to determine the ideal method for gathering data Desired Skills (Including but Not Limited to): Knowledge in Deep Learning/Neural Networks techniques, specifically NLP (Natural Language Processing, Generative AI and Computer Vision Python and SQL coding skills are indispensable Cloud experience in one of AWS - Amazon Web Service, Azure, Google Cloud Platform Proficiency oinn Machine Learning libraries and frameworks like Tensorflow, Keras, Pytorch, OpenCV, Bertl, Elmo SpaCy, NLTK, etc. Preferred- Experience creating Chatbots, and similar applications that use NLP. Object Character Recognition and Computer Vision projects like Face Recognition is a plus Experience using statistical computer languages, including Python & SQL, R is a plus to manipulate data and draw insights from large data sets Knowledge and experience in statistical and data mining techniques: GLM / Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc. Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. Ability to compile and organize statistical information retrieved and present findings to management Faculty to work toward multiple deadlines simultaneously Strong problem-solving skills with an emphasis on product development. Certification in a Cloud-Based/Machine Learning service desirable
Data Science SME (Subject matter expert) Location : London (Relocation required - Sponsorship will be provided) Experience : 12 to 18 years Job Requirements: 12 years of experience manipulating data sets and building statistical and machine learning models. Masters or Ph D in Statistics, Mathematics, Computer Science, or another quantitative field - Fluent English (written/spoken) Generative AI, Computer Vision cloud technology, NLP, Deep Learning. Experience Developing Machine Learning / Data Science models, from coding to deployment 2+ years of experience in teaching or training. 3+ Years of Hands-on Hybrid Development experience preferred. Skills Able to train/mentor/coach in coding (mandatory python and SQL, java or C++) Project Management background preferred. Knowledge of the Consulting/Sales structure. Empathy and service attitude Fast-paced Project Management experience Desirable previous international experience (US, Canada, or Europe) Leading consultants to grow and create tangible benefits and assets. Competencies Mentor / Develop / Train consultants Orientation to results Leadership Main responsibilities of the position Collecting data through means such as analyzing business results or by setting up and managing new studies Transferring data into a new format to make it more appropriate for analysis Build tools to automate data collection Compare and analyze provided statistical information to identify patterns, relationships, and problems Define and utilize statistical methods to solve industry-specific problems in varying fields, such as economics and engineering Prepare detailed reports for management and other departments by analyzing and interpreting data Train assistants and other members of the team how to properly organize findings and read data collected Design computer code using various languages to improve and update software and applications Refer to previous instances and findings to determine the ideal method for gathering data Define and utilize statistical methods to solve industry-specific problems in varying fields, such as economics and engineering Prepare detailed reports for management and other departments by analyzing and interpreting data Train assistants and other members of the team how to properly organize findings and read data collected Design computer code using various languages to improve and update software and applications Refer to previous instances and findings to determine the ideal method for gathering data Desired Skills (Including but Not Limited to): Knowledge in Deep Learning/Neural Networks techniques, specifically NLP (Natural Language Processing, Generative AI and Computer Vision Python and SQL coding skills are indispensable Cloud experience in one of AWS - Amazon Web Service, Azure, Google Cloud Platform Proficiency oinn Machine Learning libraries and frameworks like Tensorflow, Keras, Pytorch, OpenCV, Bertl, Elmo SpaCy, NLTK, etc. Preferred- Experience creating Chatbots, and similar applications that use NLP. Object Character Recognition and Computer Vision projects like Face Recognition is a plus Experience using statistical computer languages, including Python & SQL, R is a plus to manipulate data and draw insights from large data sets Knowledge and experience in statistical and data mining techniques: GLM / Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc. Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. Ability to compile and organize statistical information retrieved and present findings to management Faculty to work toward multiple deadlines simultaneously Strong problem-solving skills with an emphasis on product development. Certification in a Cloud-Based/Machine Learning service desirable
🌟 Senior Data Scientist SME & AI Architect (10+ Years Experience) 🧠 We are seeking a highly accomplished and results-oriented Senior Data Scientist Subject Matter Expert (SME) with over 10 years of experience to lead our advanced analytics and AI initiatives. This is a pivotal role requiring deep technical mastery across large-scale Big Data technologies, multi-cloud environments, and cutting-edge specialized AI domains, including Generative AI, Computer Vision, and Natural Language Processing (NLP) . You will be the principal technical leader, driving strategy, setting standards, and delivering high-impact solutions that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI) , large language models ( LLMs ), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build, and optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers ( AWS, Azure, and GCP ), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models in key specialized areas: Computer Vision: Developing and optimizing models for image recognition, object detection, and video analytics. NLP: Building sophisticated systems for sentiment analysis, entity extraction, semantic search, and RAG architectures leveraging LLMs. Generative AI: Exploring and implementing cutting-edge GenAI techniques for content creation, data augmentation, and innovative product features. SME Consulting & Mentorship: Act as the internal authority and consultant, providing technical guidance, architectural review, and mentorship to junior data scientists and engineering teams. MLOps & Governance: Establish best practices for MLOps, model monitoring, version control, and model risk governance in a multi-cloud production environment. Required Skills and Expertise (10+ Years) 1. Big Data and Cloud Mastery Programming & Big Data: 10+ years of extensive, hands-on experience with Apache Spark , with strong preference for production development using Scala . Deep expertise with Apache Hive for data querying and management. Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context. 2. Advanced AI/ML Specialization Generative AI (GenAI) & LLMs: Proven experience with the architecture and implementation of Generative AI solutions, including prompt engineering, fine-tuning, and deploying Large Language Models (LLMs) . Computer Vision: In-depth knowledge of deep learning frameworks (TensorFlow, PyTorch) and experience with Computer Vision tasks (e.g., CNNs, object detection models like YOLO). NLP: Expert practical experience in NLP techniques, including transformer models, embedding generation, and building complex text-based applications. 3. Leadership & Soft Skills Technical Leadership: Proven track record of leading complex data science projects from research to production deployment. Communication: Exceptional ability to translate complex technical findings into clear, strategic recommendations for technical and executive audiences. Mentorship: Experience mentoring and training senior engineers and data scientists. Education and Certification Master’s or Ph.D. in Computer Science, Data Science, Engineering, or a highly quantitative field. Relevant professional cloud certifications (e.g., AWS Certified Machine Learning Specialty, Google Cloud Professional Data Engineer) are highly desirable.
🌟 Senior Data Scientist SME & AI Architect (10+ Years Experience) 🧠 We are seeking a highly accomplished and results-oriented Senior Data Scientist Subject Matter Expert (SME) with over 10 years of experience to lead our advanced analytics and AI initiatives. This is a pivotal role requiring deep technical mastery across large-scale Big Data technologies, multi-cloud environments, and cutting-edge specialized AI domains, including Generative AI, Computer Vision, and Natural Language Processing (NLP) . You will be the principal technical leader, driving strategy, setting standards, and delivering high-impact solutions that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI) , large language models ( LLMs ), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build, and optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers ( AWS, Azure, and GCP ), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models in key specialized areas: Computer Vision: Developing and optimizing models for image recognition, object detection, and video analytics. NLP: Building sophisticated systems for sentiment analysis, entity extraction, semantic search, and RAG architectures leveraging LLMs. Generative AI: Exploring and implementing cutting-edge GenAI techniques for content creation, data augmentation, and innovative product features. SME Consulting & Mentorship: Act as the internal authority and consultant, providing technical guidance, architectural review, and mentorship to junior data scientists and engineering teams. MLOps & Governance: Establish best practices for MLOps, model monitoring, version control, and model risk governance in a multi-cloud production environment. Required Skills and Expertise (10+ Years) 1. Big Data and Cloud Mastery Programming & Big Data: 10+ years of extensive, hands-on experience with Apache Spark , with strong preference for production development using Scala . Deep expertise with Apache Hive for data querying and management. Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context. 2. Advanced AI/ML Specialization Generative AI (GenAI) & LLMs: Proven experience with the architecture and implementation of Generative AI solutions, including prompt engineering, fine-tuning, and deploying Large Language Models (LLMs) . Computer Vision: In-depth knowledge of deep learning frameworks (TensorFlow, PyTorch) and experience with Computer Vision tasks (e.g., CNNs, object detection models like YOLO). NLP: Expert practical experience in NLP techniques, including transformer models, embedding generation, and building complex text-based applications. 3. Leadership & Soft Skills Technical Leadership: Proven track record of leading complex data science projects from research to production deployment. Communication: Exceptional ability to translate complex technical findings into clear, strategic recommendations for technical and executive audiences. Mentorship: Experience mentoring and training senior engineers and data scientists. Education and Certification Master’s or Ph.D. in Computer Science, Data Science, Engineering, or a highly quantitative field. Relevant professional cloud certifications (e.g., AWS Certified Machine Learning Specialty, Google Cloud Professional Data Engineer) are highly desirable.
🌟 Senior Data Scientist SME & AI Architect (10+ Years Experience) 🧠 We are seeking a highly accomplished and results-oriented Senior Data Scientist Subject Matter Expert (SME) with over 10 years of experience to lead our advanced analytics and AI initiatives. This is a pivotal role requiring deep technical mastery across large-scale Big Data technologies, multi-cloud environments, and cutting-edge specialized AI domains, including Generative AI, Computer Vision, and Natural Language Processing (NLP) . You will be the principal technical leader, driving strategy, setting standards, and delivering high-impact solutions that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI) , large language models ( LLMs ), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build, and optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers ( AWS, Azure, and GCP ), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models in key specialized areas: Computer Vision: Developing and optimizing models for image recognition, object detection, and video analytics. NLP: Building sophisticated systems for sentiment analysis, entity extraction, semantic search, and RAG architectures leveraging LLMs. Generative AI: Exploring and implementing cutting-edge GenAI techniques for content creation, data augmentation, and innovative product features. SME Consulting & Mentorship: Act as the internal authority and consultant, providing technical guidance, architectural review, and mentorship to junior data scientists and engineering teams. MLOps & Governance: Establish best practices for MLOps, model monitoring, version control, and model risk governance in a multi-cloud production environment. Required Skills and Expertise (10+ Years) 1. Big Data and Cloud Mastery Programming & Big Data: 10+ years of extensive, hands-on experience with Apache Spark , with strong preference for production development using Scala . Deep expertise with Apache Hive for data querying and management. Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context. 2. Advanced AI/ML Specialization Generative AI (GenAI) & LLMs: Proven experience with the architecture and implementation of Generative AI solutions, including prompt engineering, fine-tuning, and deploying Large Language Models (LLMs) . Computer Vision: In-depth knowledge of deep learning frameworks (TensorFlow, PyTorch) and experience with Computer Vision tasks (e.g., CNNs, object detection models like YOLO). NLP: Expert practical experience in NLP techniques, including transformer models, embedding generation, and building complex text-based applications. 3. Leadership & Soft Skills Technical Leadership: Proven track record of leading complex data science projects from research to production deployment. Communication: Exceptional ability to translate complex technical findings into clear, strategic recommendations for technical and executive audiences. Mentorship: Experience mentoring and training senior engineers and data scientists. Education and Certification Master’s or Ph.D. in Computer Science, Data Science, Engineering, or a highly quantitative field. Relevant professional cloud certifications (e.g., AWS Certified Machine Learning Specialty, Google Cloud Professional Data Engineer) are highly desirable.
🌟 Senior Data Scientist SME & AI Architect (10+ Years Experience) 🧠 We are seeking a highly accomplished and results-oriented Senior Data Scientist Subject Matter Expert (SME) with over 10 years of experience to lead our advanced analytics and AI initiatives. This is a pivotal role requiring deep technical mastery across large-scale Big Data technologies, multi-cloud environments, and cutting-edge specialized AI domains, including Generative AI, Computer Vision, and Natural Language Processing (NLP) . You will be the principal technical leader, driving strategy, setting standards, and delivering high-impact solutions that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI) , large language models ( LLMs ), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build, and optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers ( AWS, Azure, and GCP ), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models in key specialized areas: Computer Vision: Developing and optimizing models for image recognition, object detection, and video analytics. NLP: Building sophisticated systems for sentiment analysis, entity extraction, semantic search, and RAG architectures leveraging LLMs. Generative AI: Exploring and implementing cutting-edge GenAI techniques for content creation, data augmentation, and innovative product features. SME Consulting & Mentorship: Act as the internal authority and consultant, providing technical guidance, architectural review, and mentorship to junior data scientists and engineering teams. MLOps & Governance: Establish best practices for MLOps, model monitoring, version control, and model risk governance in a multi-cloud production environment. Required Skills and Expertise (10+ Years) 1. Big Data and Cloud Mastery Programming & Big Data: 10+ years of extensive, hands-on experience with Apache Spark , with strong preference for production development using Scala . Deep expertise with Apache Hive for data querying and management. Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context. 2. Advanced AI/ML Specialization Generative AI (GenAI) & LLMs: Proven experience with the architecture and implementation of Generative AI solutions, including prompt engineering, fine-tuning, and deploying Large Language Models (LLMs) . Computer Vision: In-depth knowledge of deep learning frameworks (TensorFlow, PyTorch) and experience with Computer Vision tasks (e.g., CNNs, object detection models like YOLO). NLP: Expert practical experience in NLP techniques, including transformer models, embedding generation, and building complex text-based applications. 3. Leadership & Soft Skills Technical Leadership: Proven track record of leading complex data science projects from research to production deployment. Communication: Exceptional ability to translate complex technical findings into clear, strategic recommendations for technical and executive audiences. Mentorship: Experience mentoring and training senior engineers and data scientists. Education and Certification Master’s or Ph.D. in Computer Science, Data Science, Engineering, or a highly quantitative field. Relevant professional cloud certifications (e.g., AWS Certified Machine Learning Specialty, Google Cloud Professional Data Engineer) are highly desirable.
🌟 Senior Data Scientist SME & AI Architect (10+ Years Experience) 🧠 We are seeking a highly accomplished and results-oriented Senior Data Scientist Subject Matter Expert (SME) with over 10 years of experience to lead our advanced analytics and AI initiatives. This is a pivotal role requiring deep technical mastery across large-scale Big Data technologies, multi-cloud environments, and cutting-edge specialized AI domains, including Generative AI, Computer Vision, and Natural Language Processing (NLP) . You will be the principal technical leader, driving strategy, setting standards, and delivering high-impact solutions that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI) , large language models ( LLMs ), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build, and optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers ( AWS, Azure, and GCP ), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models in key specialized areas: Computer Vision: Developing and optimizing models for image recognition, object detection, and video analytics. NLP: Building sophisticated systems for sentiment analysis, entity extraction, semantic search, and RAG architectures leveraging LLMs. Generative AI: Exploring and implementing cutting-edge GenAI techniques for content creation, data augmentation, and innovative product features. SME Consulting & Mentorship: Act as the internal authority and consultant, providing technical guidance, architectural review, and mentorship to junior data scientists and engineering teams. MLOps & Governance: Establish best practices for MLOps, model monitoring, version control, and model risk governance in a multi-cloud production environment. Required Skills and Expertise (10+ Years) 1. Big Data and Cloud Mastery Programming & Big Data: 10+ years of extensive, hands-on experience with Apache Spark , with strong preference for production development using Scala . Deep expertise with Apache Hive for data querying and management. Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context. 2. Advanced AI/ML Specialization Generative AI (GenAI) & LLMs: Proven experience with the architecture and implementation of Generative AI solutions, including prompt engineering, fine-tuning, and deploying Large Language Models (LLMs) . Computer Vision: In-depth knowledge of deep learning frameworks (TensorFlow, PyTorch) and experience with Computer Vision tasks (e.g., CNNs, object detection models like YOLO). NLP: Expert practical experience in NLP techniques, including transformer models, embedding generation, and building complex text-based applications. 3. Leadership & Soft Skills Technical Leadership: Proven track record of leading complex data science projects from research to production deployment. Communication: Exceptional ability to translate complex technical findings into clear, strategic recommendations for technical and executive audiences. Mentorship: Experience mentoring and training senior engineers and data scientists. Education and Certification Master’s or Ph.D. in Computer Science, Data Science, Engineering, or a highly quantitative field. Relevant professional cloud certifications (e.g., AWS Certified Machine Learning Specialty, Google Cloud Professional Data Engineer) are highly desirable.
Data Science Lead Role: Permanent Location: London (Sponsorship will be provided) Experience: 12 to 18 years Job Requirements: 12 years of experience manipulating data sets and building statistical and machine learning models. Masters or Ph D in Statistics, Mathematics, Computer Science, or another quantitative field - Fluent English (written/spoken) Generative AI, Computer Vision cloud technology, NLP, Deep Learning. Experience Developing Machine Learning / Data Science models, from coding to deployment 2+ years of experience in teaching or training. 3+ Years of Hands-on Hybrid Development experience preferred. Skills Able to train/mentor/coach in coding (mandatory python and SQL, java or C++) Project Management background preferred. Knowledge of the Consulting/Sales structure. Empathy and service attitude Fast-paced Project Management experience Desirable previous international experience (US, Canada, or Europe) Leading consultants to grow and create tangible benefits and assets. Competencies Mentor / Develop / Train consultants Orientation to results Leadership Main responsibilities of the position Collecting data through means such as analyzing business results or by setting up and managing new studies Transferring data into a new format to make it more appropriate for analysis Build tools to automate data collection Compare and analyze provided statistical information to identify patterns, relationships, and problems Define and utilize statistical methods to solve industry-specific problems in varying fields, such as economics and engineering Prepare detailed reports for management and other departments by analyzing and interpreting data Train assistants and other members of the team how to properly organize findings and read data collected Design computer code using various languages to improve and update software and applications Refer to previous instances and findings to determine the ideal method for gathering data Define and utilize statistical methods to solve industry-specific problems in varying fields, such as economics and engineering Prepare detailed reports for management and other departments by analyzing and interpreting data Train assistants and other members of the team how to properly organize findings and read data collected Design computer code using various languages to improve and update software and applications Refer to previous instances and findings to determine the ideal method for gathering data Desired Skills (Including but Not Limited to): Knowledge in Deep Learning/Neural Networks techniques, specifically NLP (Natural Language Processing, Generative AI and Computer Vision Python and SQL coding skills are indispensable Cloud experience in one of AWS - Amazon Web Service, Azure, Google Cloud Platform Proficiency oinn Machine Learning libraries and frameworks like Tensorflow, Keras, Pytorch, OpenCV, Bertl, Elmo SpaCy, NLTK, etc. Preferred- Experience creating Chatbots, and similar applications that use NLP. Object Character Recognition and Computer Vision projects like Face Recognition is a plus Experience using statistical computer languages, including Python & SQL, R is a plus to manipulate data and draw insights from large data sets Knowledge and experience in statistical and data mining techniques: GLM / Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc. Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. Ability to compile and organize statistical information retrieved and present findings to management Faculty to work toward multiple deadlines simultaneously Strong problem-solving skills with an emphasis on product development. Certification in a Cloud-Based/Machine Learning service desirable
🚀 We're Hiring: UK/US Technical Recruiter (UK Shift) 📍 Location: Remote 🕒 Type: Full-time | Permanent 💼 Level: Junior Experience : 2 to 5 Years Education : Bachelors. Job Summary: A recruiter is responsible for finding, attracting, and hiring candidates for open positions within an organization. Their duties include understanding hiring needs, sourcing candidates through various channels, screening resumes, scheduling interviews, negotiating job offers, and managing the full hiring life cycle to ensure a positive candidate experience. Must have 360 degree end to end recruitment experience Key responsibilities Job description creation : Write and post job descriptions to attract qualified candidates. Candidate sourcing : Find potential employees through professional networks, social media, job boards, colleges, and other sources. Communication: Candidate must have fluent & strong communication skills. Screening and evaluation : Review resumes, applications, and conduct initial screenings to assess candidate qualifications. Interview coordination : Schedule and coordinate interviews between candidates and hiring managers. Collaboration : Work closely with hiring managers to understand their requirements for open roles. Offer negotiation : Manage the process of extending job offers and negotiating compensation and benefits. Relationship management : Build and maintain a pipeline of candidates for future hiring needs. Market awareness : Stay up-to-date on hiring trends and best practices in the labor market. Onboarding : Facilitate the onboarding process for new hires.
Data Science SME (Subject matter expert) Location : London (Relocation required - Sponsorship will be provided) Experience : 12 to 18 years CTC: 4000 TO 4500 US dollars Job Requirements: 12 years of experience manipulating data sets and building statistical and machine learning models. Masters or Ph D in Statistics, Mathematics, Computer Science, or another quantitative field - Fluent English (written/spoken) Generative AI, Computer Vision cloud technology, NLP, Deep Learning. Experience Developing Machine Learning / Data Science models, from coding to deployment 2+ years of experience in teaching or training. 3+ Years of Hands-on Hybrid Development experience preferred. Skills Able to train/mentor/coach in coding (mandatory python and SQL, java or C++) Project Management background preferred. Knowledge of the Consulting/Sales structure. Empathy and service attitude Fast-paced Project Management experience Desirable previous international experience (US, Canada, or Europe) Leading consultants to grow and create tangible benefits and assets. Competencies Mentor / Develop / Train consultants Orientation to results Leadership Main responsibilities of the position Collecting data through means such as analyzing business results or by setting up and managing new studies Transferring data into a new format to make it more appropriate for analysis Build tools to automate data collection Compare and analyze provided statistical information to identify patterns, relationships, and problems Define and utilize statistical methods to solve industry-specific problems in varying fields, such as economics and engineering Prepare detailed reports for management and other departments by analyzing and interpreting data Train assistants and other members of the team how to properly organize findings and read data collected Design computer code using various languages to improve and update software and applications Refer to previous instances and findings to determine the ideal method for gathering data Define and utilize statistical methods to solve industry-specific problems in varying fields, such as economics and engineering Prepare detailed reports for management and other departments by analyzing and interpreting data Train assistants and other members of the team how to properly organize findings and read data collected Design computer code using various languages to improve and update software and applications Refer to previous instances and findings to determine the ideal method for gathering data Desired Skills (Including but Not Limited to): Knowledge in Deep Learning/Neural Networks techniques, specifically NLP (Natural Language Processing, Generative AI and Computer Vision Python and SQL coding skills are indispensable Cloud experience in one of AWS - Amazon Web Service, Azure, Google Cloud Platform Proficiency oinn Machine Learning libraries and frameworks like Tensorflow, Keras, Pytorch, OpenCV, Bertl, Elmo SpaCy, NLTK, etc. Preferred- Experience creating Chatbots, and similar applications that use NLP. Object Character Recognition and Computer Vision projects like Face Recognition is a plus Experience using statistical computer languages, including Python & SQL, R is a plus to manipulate data and draw insights from large data sets Knowledge and experience in statistical and data mining techniques: GLM / Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc. Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. Ability to compile and organize statistical information retrieved and present findings to management Faculty to work toward multiple deadlines simultaneously Strong problem-solving skills with an emphasis on product development. Certification in a Cloud-Based/Machine Learning service desirable
Senior Technical Recruiter: UK & US Focus 🚀 We are seeking a seasoned and results-driven Senior Technical Recruiter to join our global Talent Acquisition team. The ideal candidate will have 5+ years of dedicated technical recruiting experience with a mandatory track record of successfully sourcing, engaging, and closing candidates across both the UK and US markets . You will be instrumental in scaling our engineering, product, and data teams in these critical international regions by managing complex requisition loads and acting as a strategic talent advisor. Key Responsibilities International Full-Cycle Recruitment: Own and manage the entire recruitment life cycle for senior-level and niche technical roles primarily based in the United Kingdom and the United States . This includes requisition intake, sourcing, screening, scheduling, offer negotiation, and closing. Strategic Sourcing & Pipeline Generation: Design and execute advanced, multi-regional sourcing strategies to build robust pipelines of passive candidates for highly competitive roles (e.g., Senior Software Engineers, Cloud Architects, Data Scientists, and Leadership roles). Market Expertise & Compensation: Act as a Subject Matter Expert (SME) on the specific nuances of the UK and US technology job markets, including providing data-driven insights on compensation benchmarks, visa requirements, and cultural differences to hiring managers. Stakeholder Consultation: Partner closely with Executive leadership and hiring managers in the US and UK to define role requirements, establish efficient interview processes, and ensure alignment between business needs and talent acquisition strategy. Candidate Experience: Deliver a best-in-class, consistent, and positive candidate experience across different time zones and cultural contexts. Compliance & Governance: Ensure all recruiting activities adhere to local employment laws and regulations (e.g., GDPR in the UK, Equal Employment Opportunity in the US). ATS & Reporting: Maintain meticulous records within the Applicant Tracking System (ATS) and provide regular reporting on pipeline health, diversity metrics, and key performance indicators (KPIs) for both regions. Required Skills and Qualifications Experience: Minimum of 5+ years of dedicated experience as a Technical Recruiter. Geographic Expertise (Mandatory): Proven, hands-on working experience recruiting for roles based in both the UK (United Kingdom) and the US (United States) , including a solid understanding of corresponding labor market dynamics. Technical Acumen: Deep understanding of modern technology stacks and technical roles (e.g., proficiency in sourcing for Java/Python/Go Engineers, AWS/Azure/GCP DevOps, and sophisticated Data Science/ML roles). Sourcing Mastery: Expert proficiency in advanced sourcing techniques using LinkedIn Recruiter, GitHub, X-ray searches, and other specialized platforms to engage hard-to-find passive candidates. Negotiation & Closing: Exceptional negotiation and closing skills, particularly handling compensation and offer structures typical in high-cost-of-labor US markets and the competitive UK tech sector. Systems: Strong proficiency with an enterprise-level Applicant Tracking System (e.g., Greenhouse, Lever, Workday, or Taleo). Communication: Outstanding cross-cultural communication and presentation skills. Preferred Qualifications (A Plus) Experience with global mobility and visa sponsorship processes for the UK and/or US. Specific experience recruiting for roles within a global SaaS or FinTech company. Certification in a relevant area (e.g., AIRS Certified, LinkedIn Recruiter Expert).