Acuity Knowledge Partners
https://www.acuitykp.com/About
Acuity Knowledge Partners (Acuity) is a leading provider of bespoke research, analytics and technology solutions to the financial services sector, including asset managers, corporate and investment banks, private equity and venture capital firms, hedge funds and consulting firms. Its global network of over 6,000 analysts and industry experts, combined with proprietary technology, supports more than 500 financial institutions and consulting companies to operate more efficiently and unlock their human capital, driving revenue higher and transforming operations. Acuity is headquartered in London and operates from 10 locations worldwide.
We EMPOWER our clients to drive revenues higher. We INNOVATE using our proprietary technology and automation solutions. Finally, we enable our clients to TRANSFORM their operating model and cost base.
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We EMPOWER our clients to drive revenues higher. We INNOVATE using our proprietary technology and automation solutions. Finally, we enable our clients to TRANSFORM their operating model and cost base.
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Jobs at Acuity Knowledge Partners
Job Purpose
We are seeking a highly skilled Data Architect to join our Financial Business Automation Products group. The ideal candidate will have a deep understanding of data architecture principles, extensive experience with data modeling, and the ability to design and implement scalable data solutions in financial domains. As a Data Architect, you will develop and maintain the data strategy, governance, security, and availability for the suite of products developed by Acuity and used by Acuity clients. The individual must be familiar with Gen AI technologies and adapt at creating data strategy to allow the Gen AI based LLMs use the data infrastructure to provide relevant outcomes.
Key Responsibilities
• Platform Design and Architecture:
o Lead the design and development of the data platform architecture, ensuring scalability, performance, reliability, and security
o Define and implement Standards for data modeling, data integration, and data lifecycle management
o Well versed with modern data platform stack with end-end coverage to build large scale Data and AI solutions
o Create blueprints for data pipelines, data lakes, data warehouses, and analytical systems
o Provide technical leadership in choosing appropriate technologies for data processing, cloud compute, and storage solutions
• Technical Solutions and Roadmap: o Influence enterprise architecture design conversations and deliver sophisticated data solutions
o Work closely with leaders, data engineers, data scientists, and analysts to define and refine data platform requirements
o Lead cross-functional teams to develop and integrate new data products and solutions
o Understand business needs and translate them into data solutions and architecture roadmap that add value to the organization
• Cloud usage and Governance
o Design and implement cloud-based solutions for data processing and storage (e.g. Azure, Snowflake, Databricks, GCP etc)
o Optimize cloud resources for cost efficiency, performance, and availability
o Ensure the security and compliance of data platforms, addressing regulatory and privacy concerns
o Develop strategies to enforce data governance policies, ensuring data quality, consistency, and integrity across systems
o Design data security measures and control access to sensitive data through role-based access and encryption
• Innovation & Continuous Improvement:
o Stay up-to-date with emerging technologies and trends in data architecture, big data, cloud computing, and AI
o Recommend and lead initiatives to improve the performance, scalability, and efficiency of data processing and storage systems
o Act as the Data Architecture subject matter expert to drive the innovation for the company
• Documentation and Technical design:
o Produce detailed documentation for platform architecture, data models, and data workflows
o Well versed with technical design, diagrams, and documentation tools • AI Integration:
o Collaborate with AI/ML teams to ensure data architectures support Gen AI initiatives.
o Enable real-time and batch data processing for AI model training and deployment.
Technology and Tools:
• 10+ years experience in designing and implementing end-to-end data platforms, including data lakes, data warehouses, and data integration pipelines.
• Experience designing and developing low-latency and high-throughput enterprise grade data architecture ecosystem
• Knowledge of relational and non-relational databases, and big data technologies (e.g., Hadoop, Spark, Kafka).
• Expertise in cloud platforms Azure, Snowflake, Databricks, Github, Jenkins etc
• Strong knowledge of ETL processes and tools for real-time data processing
• Proficiency in building data solutions using tools like Apache Kafka, Apache Airflow, and dbt (Data Build Tool) and Python
• Strong understanding of SQL and data querying best practices
• Proficiency in managing and deploying solutions on cloud platforms such as Azure, Snowflake, Databricks
• Experience with data encryption, privacy, and security best practices, including GDPR compliance
• Excellent problem-solving and communication skills
• Strong scripting skills in Python, Shell, or similar languages for automation and process optimization
• Familiarity with CI/CD pipelines, version control (Git), and deployment automation tools (Jenkins, Terraform)
• Familiarity with BI tools such as Tableau, Power BI, or Looker, as well as experience working with data scientists and analysts to support analytical workloads
Machine Learning (ML)
Data Science
Amazon Web Services (AWS)Data Scientist is responsible to discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver better products. Your primary focus will be in applying Machine Learning and Generative AI techniques for data mining and statistical analysis, Text analytics using NLP/LLM and building high quality prediction systems integrated with our products. The ideal candidate should have a prior background in Generative AI, NLP (Natural Language Processing), and Computer Vision techniques. Additionally, experience in working with current state of the art Large Language Models (LLMs), and Computer Vision algorithms.
Job Responsibilities:
» Building models using best in AI/ML technology.
» Leveraging your expertise in Generative AI, Computer Vision, Python, Machine Learning, and Data Science to develop cutting-edge solutions for our products.
» Integrating NLP techniques, and utilizing LLM's in our products.
» Training/fine tuning models with new/modified training dataset.
» Selecting features, building and optimizing classifiers using machine learning techniques.
» Conducting data analysis, curation, preprocessing, modelling, and post-processing to drive data-driven decision-making.
» Enhancing data collection procedures to include information that is relevant for building analytic systems
» Working understanding of cloud platforms (AWS).
» Collaborating with cross-functional teams to design and implement advanced AI models and algorithms.
» Involving in R&D activities to explore the latest advancements in AI technologies, frameworks, and tools.
» Documenting project requirements, methodologies, and outcomes for stakeholders.
Technical skills
Mandatory
» Minimum of 5 years of experience as Machine Learning Researcher or Data Scientist.
» Master's degree or Ph.D. (preferable) in Computer Science, Data Science, or a related field.
» Should have knowledge and experience in working with Deep Learning projects using CNN, Transformers, Encoder and decoder architectures.
» Working experience with LLM's (Large Language Models) and their applications (For e.g., tuning embedding models, data curation, prompt engineering, LoRA, etc.).
» Familiarity with LLM Agents and related frameworks.
» Good programming skills in Python and experience with relevant libraries and frameworks (e.g., PyTorch, and TensorFlow).
» Good applied statistics skills, such as distributions, statistical testing, regression, etc.
» Excellent understanding of machine learning and computer vision based techniques and algorithms.
» Strong problem-solving abilities and a proactive attitude towards learning and adopting new technologies.
» Ability to work independently, manage multiple projects simultaneously, and collaborate effectively with diverse stakeholders.
Nice to have
» Exposure to financial research domain
» Experience with JIRA, Confluence
» Understanding of scrum and Agile methodologies
» Basic understanding of NoSQL databases, such as MongoDB, Cassandra
Experience with data visualization tools, such as Grafana, GGplot, etc.
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