6 Timeseries Analysis Jobs

At PwC, the focus of individuals in data and analytics engineering is to utilize advanced technologies and techniques for designing and developing robust data solutions for clients. They are instrumental in converting raw data into actionable insights, facilitating informed decision-making, and propelling business growth. Those specializing in data science and machine learning engineering at PwC concentrate on employing advanced analytics and machine learning techniques to extract insights from extensive datasets and drive data-driven decision-making. Your responsibilities will include developing predictive models, conducting statistical analysis, and creating data visualizations to tackle intricate business challenges. You will have a significant role in organizing and maintaining proprietary datasets, transforming data into insights and visualizations that steer strategic decisions for both clients and the firm. Working closely with industry leaders and various cross-functional retail and consumer advisory, tax, and assurance professional teams, you will assist in developing impactful, commercially relevant insights to integrate into thought leadership, external media engagement, demand generation, client pursuits, and delivery enablement. Preferred Knowledge and Skills: Demonstrates in-depth abilities and a proven track record of success in managing efforts to identify and address client needs: - As a critical member of a team of Retail and Consumer data scientists, you will maintain and analyze large, complex datasets to uncover insights related to consumer sentiment, future business trends/challenges, cyclical consumer events (e.g., holidays, back-to-school, Super Bowl), business strategy, pricing, promotions, customer segmentation, and supply chain optimization. - Assist in identifying new, cutting-edge datasets to enhance the firm's differentiation among competitors and clients. - Assist in building predictive models and data-led tools. - Design and implement experiments (e.g., A/B testing, market basket analysis) to assess the effectiveness of new approaches and drive continuous improvement. - Collaborate with the US team to translate analytical findings into actionable recommendations and compelling narratives. - Develop dashboards and reports using tools like Tableau, Power BI, or Looker to support self-service analytics and decision-making. - Stay abreast of industry trends, customer behavior patterns, and emerging technologies in the consumer and retail landscape. - Experience in managing high-performing data science and commercial analytics teams. - Strong SQL and Alteryx skills, proficiency in Python and/or R for data manipulation and modeling. - Experience in applying machine learning or statistical techniques to real-world business problems. - Solid understanding of key retail and consumer metrics (e.g., CLV, churn, sales velocity, basket size). - Proven ability to explain complex data concepts to non-technical stakeholders. - Experience with retail and consumer datasets such as Circana, Yodlee, Pathmatics, Similar Web, etc. - Knowledge of geospatial or time-series analysis in a retail setting. - Previous work involving pricing optimization, inventory forecasting, or omnichannel analytics.,

The Artificial Intelligence/Machine Learning Engineer position at CDM Smith involves collaborating with the Data Technology group within the Digital Engineering Solutions team to drive strategic Architecture, Engineering, and Construction (AEC) initiatives using advanced data technologies and analytics. By leveraging artificial intelligence (AI) and machine learning (ML), the individual will play a crucial role in providing actionable business insights and robust solutions for AEC professionals and client outcomes. The focus will be on utilizing advanced analytics, data science, and AI/ML to give the business a competitive edge, including understanding and managing data, architecting & engineering data for self-serve Business Intelligence (BI) and Business Analytics (BA) opportunities. As an AI/ML Engineer at CDM Smith, you will be responsible for applying state-of-the-art algorithms and techniques such as deep learning, NLP, computer vision, and time-series analysis for domain-specific use cases within the AEC domain. You will analyze large datasets to identify patterns and trends, participate in AI model testing and validation, and optimize AI/ML workflows through MLOps practices. Collaboration with Data Engineers, Data Scientists, and other stakeholders to design and implement end-to-end AI/ML solutions will be a key aspect of this role. In addition to technical responsibilities, the position requires staying updated on the latest developments in AI/ML technologies and best practices, contributing to the development of documentation, standards, and best practices for data technology, and effectively communicating complex technical concepts to both technical and non-technical audiences. Strong problem-solving, critical thinking, and communication skills are essential for successfully executing highly complex projects and generating innovative solutions to improve business processes. To qualify for this role, you should have a Bachelor's degree and 1-2 years of related experience. Equivalent additional related experience will be considered in lieu of a degree. Basic experience with building and deploying machine learning models using frameworks like TensorFlow, PyTorch, or Scikit-learn, familiarity with cloud-based AI/ML services, programming languages such as R, Python, or Scala, and knowledge of MLOps practices are required. Understanding of data privacy, security, and ethical AI principles is essential to ensure compliance with relevant standards. This position does not require any travel. Please note that CDM Smith may conduct background checks, including criminal, employment, education, and drug testing, for designated positions. Employment will be contingent upon the successful completion of these checks.,

At PwC, the focus of individuals in data and analytics engineering is on utilizing advanced technologies and techniques to design and develop robust data solutions for clients. You will be instrumental in the transformation of raw data into actionable insights, facilitating informed decision-making and fostering business growth. As a member of the data science and machine learning engineering team at PwC, your primary responsibility will be to utilize advanced analytics and machine learning techniques to extract insights from extensive datasets, thereby driving data-driven decision-making. Your tasks will include developing predictive models, conducting statistical analysis, and creating data visualizations to address complex business challenges. Your role will be essential in the organization and maintenance of proprietary datasets, transforming data into insights and visualizations that drive strategic decisions for both clients and the firm. You will collaborate closely with industry leaders and various cross-functional Health Industries advisory, tax, and assurance professional teams to generate high-impact, commercially relevant insights. These insights will be integrated into thought leadership, external media engagement, demand generation, client pursuits, and delivery enablement efforts. Preferred Knowledge And Skills: You are expected to demonstrate in-depth abilities and a proven track record of successfully managing initiatives aimed at identifying and addressing client needs. Some of the key responsibilities include: - Contributing to the identification of cutting-edge healthcare data sources that differentiate the firm from competitors and enhance value for clients. - Designing and executing experiments to measure the effectiveness of healthcare initiatives and drive continuous improvement. - Collaborating with the US team, healthcare business stakeholders, and client teams to translate analytical findings into actionable recommendations and compelling narratives supporting decision-making. - Developing dashboards and reports using tools like Tableau, Power BI, or Looker to facilitate self-service analytics, stakeholder engagement, and regulatory reporting. - Staying informed about industry trends, patient and provider behavior patterns, and emerging technologies influencing the healthcare sector. - Managing high-performing data science and commercial analytics teams with deep healthcare domain knowledge. - Demonstrating proficiency in SQL and Alteryx, as well as Python and/or R for healthcare data manipulation, modeling, and visualization. - Applying machine learning or statistical techniques to real-world healthcare challenges, such as cost forecasting, population health management, or precision medicine. - Possessing a solid understanding of key healthcare metrics and experience with healthcare datasets from various sources. - Knowledge of geospatial or time-series analysis in a healthcare context, such as site-of-care optimization and treatment seasonality. - Previous involvement in pricing strategy, access and reimbursement modeling, value-based care analytics, or health equity assessment. In summary, as a member of the data and analytics engineering team at PwC, you will play a vital role in leveraging advanced technologies to develop data solutions, extract insights, and drive data-driven decision-making in the healthcare sector. Your contributions will be crucial in addressing complex business challenges and providing strategic support to clients and the firm.,

At PwC, the focus of individuals in data and analytics engineering is on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. Playing a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at PwC will concentrate on leveraging advanced analytics and machine learning techniques to extract insights from large datasets, driving data-driven decision making. You will be involved in developing predictive models, conducting statistical analysis, and creating data visualizations to solve complex business problems. You will be crucial in organizing and maintaining proprietary datasets, transforming data into insights and visualizations that drive strategic decisions for clients and the firm. Working closely with industry leaders and various cross-functional retail and consumer advisory, tax, and assurance professional teams to develop high-impact, commercially relevant insights for thought leadership, external media engagement, demand generation, client pursuits, and delivery enablement. Demonstrates in-depth level abilities and/or a proven record of success in managing efforts with identifying and addressing client needs: - As a critical member of a team of Retail and Consumer data scientists, maintaining and analyzing large, complex datasets to uncover insights that inform topics such as consumer sentiment, future business trends/challenges, insights around cyclical consumer-related events (e.g., holidays, back-to-school, Super Bowl, etc.), business strategy, pricing, promotions, customer segmentation, and supply chain optimization. - Supporting in the identification of new, cutting-edge datasets that add to the firm's differentiation amongst competitors and clients. - Supporting in building predictive models and data-led tools. - Designing and conducting experiments (A/B testing, market basket analysis, etc.) to measure the effectiveness of new approaches and drive continuous improvement. - Partnering with the US team to translate analytical findings into actionable recommendations and compelling stories. - Developing dashboards and reports using tools like Tableau, Power BI, or Looker to support self-service analytics and decision-making. - Staying up to date and ahead of industry trends, customer behavior patterns, and emerging technologies in the consumer and retail landscape. - Having experience managing high-performing data science and commercial analytics teams. - Strong SQL and Alteryx skills and proficiency in Python and/or R for data manipulation and modeling. - Experience applying machine learning or statistical techniques to real-world business problems. - Solid understanding of key retail and consumer metrics (e.g., CLV, churn, sales velocity, basket size, etc.). - Proven ability to explain complex data concepts to non-technical stakeholders. - Experience with retail and consumer datasets such as Circana, Yodlee, Pathmatics, Similar Web, etc. - Knowledge of geospatial or time-series analysis in a retail setting. - Prior work with pricing optimization, inventory forecasting, or omnichannel analytics.,

You will be joining the Digital Engineering Solutions team at CDM Smith as an Artificial Intelligence/Machine Learning Engineer. In this role, you will work within the Data Technology group to support strategic Architecture, Engineering, and Construction (AEC) initiatives by leveraging cutting-edge data technologies and analytics. Your responsibilities will include contributing to advanced analytics and implementing AI/ML solutions to address complex business challenges within the AEC domain. You will utilize state-of-the-art algorithms and techniques such as deep learning, NLP, computer vision, and time-series analysis for domain-specific use cases. Your role will involve analyzing large datasets to identify patterns and trends and ensuring AI models perform in line with business requirements. As an AI/ML Engineer, you will collaborate with Data Engineers, Data Scientists, and other stakeholders to design and implement end-to-end AI/ML solutions. You will also be involved in optimizing AI/ML workflows by implementing MLOps practices, including CI/CD pipelines, model retraining, and version control. Additionally, staying updated on the latest developments in technology and best practices will be crucial to your role. To succeed in this position, you should have a good understanding of the software development life cycle and experience with building and deploying machine learning models using frameworks like TensorFlow, PyTorch, or Scikit-learn. Knowledge of cloud-based AI/ML services, programming languages (e.g., R, Python, Scala), and MLOps practices is essential. You must also be familiar with data privacy, security, and ethical AI principles to ensure compliance with relevant standards. Strong problem-solving, critical thinking, and communication skills are required to effectively address technical challenges and engage with both technical and non-technical audiences. Minimum qualifications for this role include a Bachelor's degree and 1-2 years of related experience. Equivalent additional experience will be considered in lieu of a degree. The position does not require any travel. Background checks, including criminal history, employment verification, and drug testing, may be conducted as per CDM Smith's policies for certain positions. As an AI/ML Engineer at CDM Smith, you will play a key role in driving innovation and delivering impactful solutions for AEC professionals and client outcomes. Your contributions to the Data Technology group will help shape the future of AI/ML in the architecture, engineering, and construction industry.,

The position of Risk Methodology Specialist at Deutsche Bank as an Assistant Vice President involves contributing to the bank's balance sheet and income statement modelling methodologies to support various end uses such as stress testing, interest rate risk in the banking book, liquidity, and planning. As an AVP, you will be responsible for managing relationships with Business/Risk/Treasury/Finance model stakeholders, executing model development protocols, critically evaluating information from multiple sources, and working independently with team leads/teams/management. The role requires a candidate with very good English communication skills to effectively coordinate and communicate with stakeholders globally. The candidate should possess people skills and be able to handle complex situations. The responsibilities also include contributing to model development, authoring model documentation, analyzing assumptions, weaknesses, and compensating controls, creating proof of concept case studies, and exploring alternative modelling approaches. The ideal candidate should have experience in model development for Banking or Capital Markets at a top-tier bank or consulting firm. Solid banking business knowledge, strong experience in R Studio and/or Python, and a degree from a top-tier institution with a quantitative concentration are essential. The role demands strong quantitative skills, including knowledge and modeling experience in areas such as PPNR, Credit Risk, Market risk, and relevant interdependencies. Proficiency in at least one programming language, strong written and verbal communication skills, and behavioral skills like Collaboration, Teamwork, Integrity, Trust, and Fairness, among others, are crucial for this role. Educational qualifications include a University graduate or equivalent degree in finance, economics, mathematics, statistics, or engineering. Masters qualifications or above would be considered an advantage. Deutsche Bank offers training, development, coaching, and a culture of continuous learning to aid progression. The bank promotes a positive, fair, and inclusive work environment where employees are empowered to excel together every day. If you are looking to excel in your career in a dynamic and supportive environment, this role at Deutsche Bank might be the right fit for you.,