
51 - 200 employees
Founded 1994
💼 Consulting
⚖️ Legal
💸 Finance
💰 Private Equity Round on 2023-01
Consulting • Legal • Finance
CFRA Research is a global leader in delivering independent and unbiased investment research and financial intelligence solutions to clients worldwide. The company specializes in providing a comprehensive range of research services, including fundamental equity research, forensic accounting research, and public policy and legal research. Catering to a diverse clientele, CFRA serves wealth management firms, institutional investors, financial advisors, and self-directed individual investors by equipping them with the necessary data and analytics to navigate market cycles and make informed investment decisions. Notably, CFRA's award-winning technology and content delivery methods enable clients to integrate its insights seamlessly into their operations, ensuring flexible and cost-effective solutions across various platforms, such as web-based or API integrations. Their expertise spans consumer, energy, financials, healthcare, and technology sectors, among others, helping clients enhance portfolio performance and mitigate risks through high-quality research and data analytics.
🔥 4 minutes ago
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51 - 200 employees
Founded 1994
💼 Consulting
⚖️ Legal
💸 Finance
💰 Private Equity Round on 2023-01
Consulting • Legal • Finance
CFRA Research is a global leader in delivering independent and unbiased investment research and financial intelligence solutions to clients worldwide. The company specializes in providing a comprehensive range of research services, including fundamental equity research, forensic accounting research, and public policy and legal research. Catering to a diverse clientele, CFRA serves wealth management firms, institutional investors, financial advisors, and self-directed individual investors by equipping them with the necessary data and analytics to navigate market cycles and make informed investment decisions. Notably, CFRA's award-winning technology and content delivery methods enable clients to integrate its insights seamlessly into their operations, ensuring flexible and cost-effective solutions across various platforms, such as web-based or API integrations. Their expertise spans consumer, energy, financials, healthcare, and technology sectors, among others, helping clients enhance portfolio performance and mitigate risks through high-quality research and data analytics.
• Lead the design and development of quantitative data engineering models, including algorithms, data pipelines, and data processing systems • Develop and maintain pipelines to ingest, clean, transform, and aggregate large volumes of data • Design and implement algorithms for data analysis, machine learning, and statistical modeling • Optimize data processing and modeling algorithms for performance, scalability, and resource utilization • Create data and model-output visualizations for stakeholders • Implement data quality checks and validation processes • Evaluate model performance using metrics and validation techniques, iterating to improve accuracy and effectiveness • Collaborate with data scientists, analysts, and business stakeholders to understand requirements and deliver insights • Document model design, implementation, evaluation, assumptions, methodologies, and results • Stay updated with trends, tools, and technologies in quantitative data engineering and data science
• Strong background in data engineering principles, including data ingestion, data processing, data transformation, and data storage, using tools and frameworks such as Apache Spark, Apache Flink, or AWS Glue • Proficiency in quantitative analysis techniques, including statistical modeling, machine learning, and data mining • Experience implementing algorithms for regression analysis, clustering, classification, and predictive modeling • Proficiency in Python, R, Java, or Scala • Experience with SQL for data querying and manipulation • Familiarity with Hadoop, Apache Kafka, Apache Hive, or AWS EMR • Experience with Matplotlib, Seaborn, or Tableau • Familiarity with PyTorch • Experience with AWS, Azure, or Google Cloud Platform • Strong software development skills, including software design patterns, Git, and software testing frameworks • Strong problem-solving, communication, and collaboration skills • Domain knowledge in finance, healthcare, or marketing • Commitment to continuous learning and staying updated with data engineering, quantitative analysis, and machine learning technologies
• 21 days of Annual Vacation • 8 sick days • 6 casual days • 1 paid Volunteer Day • Medical, Accidental & Term Life Insurance • Telehealth, OPD • Competitive pay • Annual Performance Bonus
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