20 Timeseries Analysis Jobs

At PwC, our team in data and analytics engineering focuses on utilizing advanced technologies and techniques to design and develop robust data solutions for clients. You will be instrumental in the process of transforming raw data into actionable insights, facilitating informed decision-making, and propelling business growth. If you are in data science and machine learning engineering at PwC, your primary focus will be on harnessing 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 address complex business challenges. In this role, you will have a vital role in organizing and maintaining proprietary datasets, converting data into insights and visualizations that steer strategic decisions for both our clients and the firm. Your collaboration will be key with industry leaders and various cross-functional retail and consumer advisory, tax, and assurance professional teams to develop impactful, commercially relevant insights. These insights will be integrated into thought leadership, external media engagement, demand generation, client pursuits, and delivery enablement initiatives. Key Skills Preferred: - Demonstrates in-depth abilities and a successful track record in managing efforts to identify and address client needs. - Work as a crucial member of a team of Retail and Consumer data scientists, analyzing large, complex datasets to reveal insights on consumer sentiment, future business trends, challenges, consumer-related events, business strategy, pricing, promotions, customer segmentation, and supply chain optimization. - Assist in the discovery of innovative datasets that contribute to the firm's competitive edge among rivals and clients. - Aid in constructing predictive models and data-driven tools. - Plan and execute experiments such as A/B testing, market basket analysis to evaluate 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 facilitate self-service analytics and decision-making. - Stay updated on industry trends, customer behavior patterns, and emerging technologies in the consumer and retail sector. - Proficiency in managing high-performing data science and commercial analytics teams. - Strong skills in SQL and Alteryx, and proficiency in Python and/or R for data manipulation and modeling. - Experience in applying machine learning or statistical techniques to real-world business challenges. - Sound understanding of key retail and consumer metrics such as CLV, churn, sales velocity, basket size, etc. - Ability to explain complex data concepts to non-technical stakeholders effectively. - Familiarity with retail and consumer datasets like Circana, Yodlee, Pathmatics, Similar Web, etc. - Knowledge of geospatial or time-series analysis in a retail context. - Previous involvement in pricing optimization, inventory forecasting, or omnichannel analytics.,

marketfeed is a Y Combinator-funded seed-stage startup founded by Sharique Samsudheen & Sooraj E in 2020. We offer an automated trading platform to assist users in earning returns through sophisticated options trading strategies. Our platform has garnered over 1.5 million followers on social media and 400,000 app users, showcasing consistent month-on-month growth of over 20%. To date, our users have collectively invested over Rs. 250 crores through marketfeed. We are driven by a team of 50+ passionate individuals dedicated to helping people grow wealth. We are currently looking for a highly skilled and analytical Quantitative Researcher to join our dynamic team in Bengaluru. In this role, you will be responsible for developing, testing, and implementing quantitative models and trading strategies to identify market opportunities and enhance trading performance. Your contributions will play a crucial role in democratizing profitable trading for our extensive user base. The ideal candidate for this position should possess: - 3+ years of hands-on quantitative research experience with a proven track record of live deployment. - A degree in Mathematics, Statistics, Physics, Computer Science, Engineering, or Financial Engineering from a reputable institute. - Proficiency in programming languages such as Python, R, or C++. - Practical knowledge in setting up and managing complete research frameworks. - Ability to analyze extensive datasets, historical market data, and alternative data sources. - Expertise in quantitative model development, algorithm optimization, and risk assessment. - Understanding of Delta 1 and Options strategies at scale, including market microstructure and order book dynamics. - Excellent communication skills to effectively convey complex findings to diverse stakeholders. Key Responsibilities: 1. Research & Model Development: Design, develop, and refine mathematical and statistical models to predict market trends and price movements. 2. Data Analysis: Analyze large datasets to uncover actionable insights and trading signals. 3. Strategy Implementation: Collaborate with traders and developers to implement trading strategies in live environments. 4. Algorithm Optimization: Optimize algorithms for speed, accuracy, and risk management. 5. Risk Assessment: Evaluate and mitigate risks associated with trading strategies and market conditions. 6. Tool Development: Guide, build, and maintain tools for data visualization, simulation, and performance analysis. 7. Market Research: Stay updated on market trends, financial instruments, and regulatory changes. 8. Collaboration: Work closely with quantitative developers, traders, and portfolio managers to ensure seamless execution of strategies. Preferred Skills: - Experience with MFT strategies in Delta 1 and Options, particularly arbitrage or market making. - Strong grasp of machine learning techniques such as regression, time-series analysis, and neural networks. What's In It For You: - Opportunity to work on innovative trading products and financial instruments. - Flexible leave policy and working hours for a healthy work-life balance. - Comprehensive health insurance covering physical and mental health, including unlimited doctor consultations and dental care. - Competitive salary with lucrative ESOPs, annual team retreats, and a dog-friendly office environment. Interviewing Process: Our structured hiring process includes initial screenings for fit, technical discussions to evaluate mathematical ability and coding proficiency, and a final round interview with the founders to ensure cultural alignment and mission alignment.,

As a skilled Data Scientist with 4 years of experience, you will be responsible for leveraging your expertise in data analysis, machine learning, and statistical modeling to extract actionable insights from complex datasets. Your role will involve collaborating with cross-functional teams to solve business problems, develop predictive models, and contribute to data-driven decision-making processes. Your key responsibilities will include collecting, cleaning, and preprocessing large datasets from diverse sources to ensure data quality and integrity. You will design, develop, and implement machine learning models and algorithms to address business challenges, as well as perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies. Additionally, you will build and validate predictive and prescriptive models using statistical techniques and tools, collaborating with stakeholders to translate business requirements into data-driven solutions. Furthermore, you will create visualizations and dashboards to effectively communicate findings to technical and non-technical audiences. You will also optimize and fine-tune existing models to enhance accuracy, performance, and scalability, while staying current with industry trends, emerging tools, and advancements in data science and AI. Documenting methodologies, processes, and results for reproducibility and knowledge sharing will also be part of your responsibilities. To qualify for this role, you should hold a Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field, along with at least 4 years of professional experience as a Data Scientist or in a similar role. Proficiency in programming languages such as Python or R for data analysis and modeling is required, as well as strong experience with machine learning frameworks like TensorFlow, PyTorch, and Scikit-learn. Expertise in statistical analysis, hypothesis testing, and experimental design is essential, along with hands-on experience with SQL for querying and manipulating large datasets. Knowledge of big data technologies such as Hadoop and Spark would be advantageous. Additionally, you should possess the ability to work in a collaborative environment, adapt to new AI technologies, and demonstrate excellent problem-solving skills. Strong communication skills are necessary to present complex findings in a clear and concise manner. Preferred skills for this role include experience with cloud platforms like AWS, Azure, and Google Cloud for data processing and model deployment, a background in natural language processing (NLP), computer vision, or time-series analysis, and understanding of software development practices such as version control with Git and CI/CD pipelines. In conclusion, as a valued member of our dynamic team at NewRocket, you will have the opportunity to work on cutting-edge data science projects, collaborate with top enterprise leaders, and contribute to the creation of new kinds of experiences for our customers. If you are passionate about data science and eager to make a meaningful impact, we invite you to join our crew and be part of our journey to #GoBeyondWorkflows.,

As an AI Research Engineer at Mantra Softech, a technology leader in biometric solutions venturing into AI-powered smart home devices, you will play a crucial role in shaping the future of connected living. Your primary responsibility will be to lead initiatives in LLMs, Edge AI, sensor fusion, ML Models, and natural language interfaces to develop AI-powered experiences across innovative smart home devices. You will be instrumental in designing and developing GenAI-driven AI agents capable of interpreting multimodal inputs and executing context-aware actions. Your role will involve driving initiatives in agentic AI frameworks, architecting LLMOps workflows, and deploying real-time AI applications across cloud and edge environments with a focus on performance and reliability. To excel in this role, you must have a proven track record of designing, deploying, and delivering AI/ML systems into production, with expertise in LLMs, GenAI pipelines, prompt engineering, and agentic AI. Proficiency in Python (and/or C/C++), PyTorch/TensorFlow, and AI/ML frameworks is essential, along with experience in LLMOps, time-series analysis, model optimization, and SQL. Preferred skills for this role include familiarity with LangChain, LlamaIndex, digital twins, telemetry, AI safety, cloud deployment, and microservices. A master's degree in AI/ML, Computer Science, or a related field from a reputed institute, coupled with 4-6 years of industry experience in GenAI and production deployments, is required. If you are passionate about GenAI applications, AI agents, and transforming natural language prompts into actionable insights, this role offers you the opportunity to work on cutting-edge AI projects that will drive the future of connected living. Join us at Mantra Softech and be part of a world-class AI team that is revolutionizing the way we interact with smart home devices.,

At PwC, we are focused on leveraging advanced technologies and techniques in data and analytics engineering to design and develop robust data solutions for our clients. As a member of our team, you will play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. In the field of data science and machine learning engineering at PwC, you will be responsible for leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision-making. Your work will involve developing predictive models, conducting statistical analysis, and creating data visualizations to solve complex business problems. Your role will also involve organizing and maintaining proprietary datasets, as well as transforming data into insights and visualizations that drive strategic decisions for our clients and the firm. You will collaborate closely with industry leaders and cross-functional teams to develop high-impact insights that can be used in various aspects such as thought leadership, external media engagement, demand generation, client pursuits, and delivery enablement. Preferred knowledge and skills for this role include the ability to manage efforts in identifying and addressing client needs, maintaining and analyzing large, complex datasets to uncover insights, supporting the identification of new datasets, building predictive models, designing and conducting experiments, translating analytical findings into actionable recommendations, developing dashboards and reports, staying up to date with industry trends, managing data science and commercial analytics teams, proficiency in SQL, Alteryx, Python, and/or R, applying machine learning and statistical techniques, explaining complex data concepts to non-technical stakeholders, working with industry-specific datasets and vendors, knowledge of geospatial or time-series analysis, and prior experience in commercial analytics and insights.,

You will focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients at PwC. Your role will involve transforming raw data into actionable insights to enable informed decision-making and drive business growth. Additionally, you will work on developing predictive models, conducting statistical analysis, and creating data visualizations to solve complex business problems. Your responsibilities will include organizing and maintaining proprietary datasets, transforming data into insights and visualizations to drive strategic decisions for clients and the firm. You will collaborate closely with industry leaders and cross-functional teams to develop high-impact insights for thought leadership, external media engagement, demand generation, client pursuits, and delivery enablement. As a critical member of the data science team, you will analyze large, complex datasets to uncover insights related to Industrial Products. You will also support the identification of new datasets to differentiate the firm and assist in building predictive models and data-led tools. Moreover, you will design and conduct experiments to measure the effectiveness of new approaches and partner with teams to translate analytical findings into actionable recommendations and compelling stories. It is essential to develop dashboards and reports using tools like Tableau, Power BI, or Looker for self-service analytics and decision-making. Staying updated on industry trends, customer behavior patterns, and emerging technologies is crucial in this role. Preferred skills include managing data science and commercial analytics teams, proficiency in SQL, Alteryx, Python, and/or R for data manipulation and modeling, applying machine learning or statistical techniques to business problems, explaining complex data concepts to non-technical stakeholders, working with industry-specific datasets and vendors, knowledge of geospatial or time-series analysis, and experience with commercial analytics and insights.,

At PwC, we focus on leveraging advanced technologies and techniques to design and develop robust data solutions for our clients. You will play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. As part of the data science and machine learning engineering team, you will extract insights from large datasets and drive data-driven decision making. Your responsibilities will include developing predictive models, conducting statistical analysis, and creating data visualizations to solve complex business problems. Your role will involve organizing and maintaining proprietary datasets, transforming data into insights and visualizations that drive strategic decisions for our clients and the firm. You will collaborate closely with industry leaders and cross-functional teams to develop high-impact insights for thought leadership, media engagement, client pursuits, and delivery enablement. Preferred Knowledge And Skills: - Manage efforts with identifying and addressing client needs, maintaining and analyzing large, complex datasets to uncover insights. - Identify new, cutting-edge datasets to differentiate the firm amongst competitors and clients. - Build predictive models, design and conduct experiments, and translate analytical findings into actionable recommendations. - Develop dashboards and reports using tools like Tableau, Power BI, or Looker to support self-service analytics. - Stay updated on industry trends, customer behavior patterns, and emerging technologies. - Experience managing high-performing data science and commercial analytics teams. - Proficiency in SQL, Alteryx, Python, and/or R for data manipulation and modeling. - Apply machine learning and statistical techniques to real-world business problems. - Explain complex data concepts to non-technical stakeholders. - Work with industry-specific datasets and vendors, and knowledge of geospatial or time-series analysis. - Prior experience with commercial analytics and insights.,

As a Quantitative Researcher at Quance Research Capital LLP, you will play a pivotal role in developing and testing automated quant trading strategies using sophisticated statistical techniques. Your responsibilities will include designing high-frequency trading strategies by analyzing market data, identifying patterns, exploring market inefficiencies, and developing algorithms to capitalize on opportunities that exist for a fraction of a second. You will have access to market data from various exchanges worldwide and will be expected to conceptualize strategies, continuously improve mathematical models, and translate algorithms into code. Your role will involve modeling gigabytes of data daily, utilizing Python, R, and C++ to analyze market microstructure and identify trading signals. You will also be responsible for improving existing trading strategies, back-testing and implementing new models in a live trading environment, conducting statistical analysis to refine monetization systems, and producing business-critical reports. Additionally, you will trade a vast portfolio and work towards enhancing the organization's trading strategies across global exchanges. To excel in this role, you should possess a deep quantitative/programming background with a graduate degree in Statistics, Engineering, Computer Science, Mathematics, Operations Research, Economics, or a related quantitative field. A minimum of 2 years of experience, preferably in High-Frequency Trading (HFT) or Algo firms, is required. Strong knowledge of probability and statistics, as well as proficiency in Python, R, and C++, is essential. Familiarity with data science, machine learning, market microstructure, and Linux will be advantageous. We are seeking self-motivated individuals with a keen interest in financial markets, commodities, and machine learning/AI techniques. If you have expertise in ML-based systems and a passion for trading, we encourage you to apply. Strong analytical skills, attention to detail, ability to work under pressure, and a collaborative mindset are crucial for success in this role. Join us at Quance Research Capital LLP and be part of a dynamic team driving innovation in the financial markets.,

As an AI/ML, Data Science Engineer, you will have the exciting opportunity to be at the forefront of building the future of Observability powered by AI agents. If you are enthusiastic about working on Time-Series and Causal Analysis at scale, and eager to innovate and construct time-series LLMs, then this is the perfect role for you. The fast-paced startup environment will allow you to make a real impact as we redefine Observability with Agentic AI. Joining our team means you will have the chance to innovate alongside a dynamic team that is developing next-gen AI-driven infrastructure. Your contributions will play a significant role in shaping the next generation of Observability. As an early member of our AI/ML team, you will be hands-on in applying time-series and causal analytics to solve complex observability problems. Your responsibilities will include working on building model evaluation frameworks and innovating on constructing time-series LLMs. You will get the best of both worlds - the agility and innovation of a startup, coupled with the challenge of discovering deep hidden behavior patterns and causal relationships using traditional and new state-of-the-art methods. Working closely with a seasoned and talented founding team, who have successfully built multiple billion-dollar products from the ground up, will provide you with valuable insights into how things are developed from scratch in deep-technology startups. In this role, you will need to have hands-on experience with time-series algorithms, causal analytics, building model evaluations at scale, and deploying them in production. Additionally, expertise in Python, PyTorch, Causal Analysis & Time Series Analysis libraries is required. Your extensive experience in Time-Series Analysis, proven ability in building, deploying, and optimizing time-series models, expertise in Causal Analytics, and hands-on experience with large-scale structured and unstructured datasets will be crucial. You should have a deep understanding of MLOps pipelines, be proficient in LLM fine-tuning & distillation, and have a track record of developing robust, scalable ML pipelines. Passion for AI and leveraging cutting-edge technologies, curiosity, thinking differently to challenge inefficiencies in the status quo, and a problem-solver mindset are qualities we are looking for in potential candidates. Join us to be a key player in defining the future of Observability. If you are seeking a high-impact, high-growth opportunity, we would love to have a conversation with you.,

As an experienced professional with over 2 years of experience, you will be responsible for designing, developing, and deploying Machine Learning / Artificial Intelligent models to address real-world challenges within our software products. Your role will involve collaborating with product managers, developers, and data engineers to establish AI project objectives and specifications. Additionally, you will be tasked with cleaning, processing, and analyzing extensive datasets to uncover valuable patterns and insights. Your expertise will be utilized in implementing and refining models using frameworks like TensorFlow, PyTorch, or Scikit-learn. You will also play a crucial role in creating APIs and services to seamlessly integrate AI models into production environments. Monitoring model performance and conducting retraining as necessary to uphold accuracy and efficiency will be part of your regular duties. It is essential to keep yourself abreast of the latest developments in AI/ML and assess their relevance to our projects. To excel in this role, you should hold a Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or a related discipline. A strong grasp of machine learning algorithms, including supervised, unsupervised, and reinforcement learning, is imperative. Proficiency in Python and ML libraries such as NumPy, pandas, TensorFlow, Keras, and PyTorch is required. Familiarity with NLP, computer vision, or time-series analysis will be advantageous. Experience with model deployment tools and cloud platforms like AWS, GCP, or Azure is preferred. Knowledge of software engineering practices, encompassing version control (Git), testing, and CI/CD, is also essential. Candidates with prior experience in a product-based or tech-driven startup environment, exposure to deep learning, recommendation systems, or predictive analytics, and an understanding of ethical AI practices and model interpretability will be highly regarded. This is a full-time position requiring you to work during day shifts at our in-person work location.,

You will be joining our team as a Senior Data Scientist with expertise in Artificial Intelligence (AI) and Machine Learning (ML). The ideal candidate should possess a minimum of 5-7 years of experience in data science, focusing on AI/ML applications. You are expected to have a strong background in various ML algorithms, programming languages such as Python, R, or Scala, and data processing frameworks like Apache Spark. Proficiency in data visualization tools and experience in model deployment using Docker, Kubernetes, and cloud services will be essential for this role. Your responsibilities will include end-to-end AI/ML project delivery, from data processing to model deployment. You should have a good understanding of statistics, probability, and mathematical concepts used in AI/ML. Additionally, familiarity with big data tools, natural language processing techniques, time-series analysis, and MLOps will be advantageous. As a Senior Data Scientist, you are expected to lead cross-functional project teams and manage data science projects in a production setting. Your problem-solving skills, communication skills, and curiosity to stay updated with the latest advancements in AI and ML are crucial for success in this role. You should be able to convey technical insights clearly to diverse audiences and quickly adapt to new technologies. If you are an innovative, analytical, and collaborative team player with a proven track record in AI/ML project delivery, we invite you to apply for this exciting opportunity.,

Offshore Software Solutions is looking for a Data Scientist with 3-5 years of experience in analyzing health data from devices like smartwatches and fitness trackers. The role involves developing custom machine learning models using TensorFlow to derive actionable insights for improving health monitoring and user well-being. Your responsibilities will include analyzing health data from wearables, developing and deploying machine learning models, collaborating with cross-functional teams, preprocessing data, ensuring privacy standards compliance, optimizing models for accuracy, and presenting findings to stakeholders. Additionally, you will stay updated on the latest machine learning research related to health data from wearable devices. Requirements for this role include a Bachelor's or Masters degree in Data Science or related field, 3+ years of data analysis experience, expertise in TensorFlow, knowledge of deep learning and neural networks, proficiency in Python and data science libraries, familiarity with health data metrics, experience with data visualization tools and databases, and strong problem-solving skills. Preferred qualifications include working with wearable device APIs, understanding time-series analysis and anomaly detection, experience in edge computing, and good communication skills for effective collaboration. If you are passionate about leveraging data science to improve health monitoring and user well-being, and possess the required skills and qualifications, we encourage you to apply for this exciting opportunity at Offshore Software Solutions in Mohali, Punjab.,

You should have a Bachelor's Degree in a technical or quantitative field from an accredited college or university. A Master's or PhD in Computer Science, Statistics, Mathematics, Engineering, Bioinformatics, Physics, Operations Research, or related fields is preferred. You must have at least 10 years of relevant experience in Machine Learning and Statistics. A strong mathematical background is required, with the ability to understand algorithms and methods both mathematically and intuitively. Your primary responsibilities will include translating business objectives into analytic approaches, identifying data sources to support analysis, and analyzing structured and unstructured data using advanced statistical methods, deep learning, and Generative AI. You will need to perform exploratory data analyses, generate and test working hypotheses, prepare and analyze historical data, and identify patterns. Proficiency in Python and SQL is essential, along with experience in working with open-source packages and commercial/enterprise applications. You should be comfortable with machine learning and statistical methods such as regression, classification, clustering, ensemble and tree-based models, and time-series analysis. Prior experience or understanding in ML Ops in any cloud platform is required. You should have a strong background in Generative AI, particularly with tools like ChatGPT and CoPilot, and hands-on experience in using APIs to integrate with CoPilot and fabric. Exposure to the Microsoft Tech Stack ecosystem is necessary, along with familiarity with Azure Document Intelligence and Azure Machine Learning for model training and deployment. Additionally, you should be familiar with at least one of the following: Azure AI Language, Azure AI Vision. As part of your role, you will need to communicate results and educate others through reports and presentations. Familiarity with DevOps, code version control, and software development coding best practices is essential. Candidates must hold at least two of the following certifications from Azure: DP-203, MB260, DP-900, AI-102, AI-900.,

As a Data Engineer at CLOUDSUFI, a Google Cloud Premier Partner, you will be responsible for designing, developing, and deploying graph database solutions using Neo4j for economic data analysis and modeling. Your expertise in graph database architecture, data pipeline development, and production system deployment will play a crucial role in this position. Your key responsibilities will include designing and implementing Neo4j graph database schemas for complex economic datasets, developing efficient graph data models, creating and optimizing Cypher queries, building graph-based data pipelines for real-time and batch processing, architecting scalable data ingestion frameworks, developing ETL/ELT processes, implementing data validation and monitoring systems, and building APIs and services for graph data access and manipulation. In addition, you will be involved in deploying and maintaining Neo4j clusters in production environments, implementing backup and disaster recovery solutions, monitoring database performance, optimizing queries, managing capacity planning, and establishing CI/CD pipelines for graph database deployments. You will also collaborate with economists and analysts to translate business requirements into graph solutions. To be successful in this role, you should have 5-10 years of experience, with a background in BTech / BE / MCA / MSc Computer Science. You should have expertise in Neo4j database development, graph modeling, Cypher Query Language, programming languages such as Python, Java, or Scala, data pipeline tools like Apache Kafka and Apache Spark, and cloud platforms like AWS, GCP, or Azure with containerization. Experience with graph database administration, performance tuning, distributed systems, database clustering, data warehousing concepts, and dimensional modeling will be beneficial. Knowledge of financial datasets, market data, economic indicators, data governance, and compliance in financial services is also desired. Preferred qualifications include Neo4j Certification, a Master's degree in Computer Science, Economics, or a related field, 5+ years of industry experience in financial services or economic research, and additional skills in machine learning on graphs, network analysis, and time-series analysis. You will work in a technical environment that includes Neo4j Enterprise Edition with APOC procedures, Apache Kafka, Apache Spark, Docker, Kubernetes, Git, Jenkins/GitLab CI, and monitoring tools like Prometheus, Grafana, and ELK stack. Your application should include a portfolio demonstrating Neo4j graph database projects, examples of production graph systems you've built, and experience with economic or financial data modeling.,

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.,