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  • FinLex: An effective use of word embeddings for financial lexicon generation
    Sanjiv Das, Michele Donini, Bilal Zafar, John He, Krishnaram Kenthapadi
    The Journal of Finance and Data Science (JFDS)
    2021
    We present a simple and effective methodology for the generation of lexicons (word lists) that may be used in natural language scoring applications. In particular, in the finance industry, word lists have become ubiquitous for sentiment scoring. These have been derived from dictionaries such as the Harvard Inquirer and require manual curation. Here, we present an automated approach to the curation of lexicons
    Conversational AI
  • Context, language modeling, and multimodal data in finance
    Sanjiv Das, Connor Giggins, John He, George Karypis, Sandeep Krishnamurthy, Mitali Mahajan, Nagpurnanand Prabhala, Dylan Slack, Rob van Dusen, Shenghua Yue, Sheng Zha, Shuai Zheng
    The Journal of Financial Data Science Summer
    2021
    The authors enhance pretrained language models with Securities and Exchange Commission filings data to create better language representations for features used in a predictive model. Specifically, they train RoBERTa class models with additional financial regulatory text, which they denote as a class of RoBERTa-Fin models. Using different datasets, the authors assess whether there is material improvement
    Conversational AI
  • Forecast hedging and calibration
    Dean Foster, Sergiu Hart
    Journal of Political Economy
    2021
    Calibration means that forecasts and average realized frequencies are close. We develop the concept of forecast hedging, which consists of choosing the forecasts so as to guarantee that the expected track record can only improve. This yields all the calibration results by the same simple basic argument while differentiating between them by the forecast-hedging tools used: deterministic and fixed point based
    Economics
  • Have your text and use it too! End-to-end neural data-to-text generation with semantic fidelity
    Hamza Harkous, Isabel Groves, Amir Saffari
    COLING 2020
    2020
    End-to-end neural data-to-text (D2T) generation has recently emerged as an alternative to pipeline-based architectures. However, it has faced challenges generalizing to new domains and generating semantically consistent text. In this work, we present DATATUNER, a neural, end-to-end data-to-text generation system that makes minimal assumptions about the data representation and target domain. We take a two-stage
    Related: Automatically generating text from structured data
    Conversational AI
  • Deep PQR: Solving inverse reinforcement learning using anchor actions
    Sinong Geng, Houssam Nassif, Carlos A. Manzanares, A. Max Reppen, Ronnie Sircar
    ICML 2020
    2020
    We propose a reward function estimation framework for inverse reinforcement learning with deep energy-based policies. We name our method PQR, as it sequentially estimates the Policy, the Qfunction, and the Reward function. PQR does not assume that the reward solely depends on the state, instead it allows for a dependency on the choice of action. Moreover, PQR allows for stochastic state transitions. To
    Economics
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Intern - Economics, WW Returns & ReComm Tech& Inn
US, WA, Bellevue
Amazon is committed to exceeding customer expectations. In the Returns and Recommerce organization, we seek to improve customer satisfaction with the items they buy on Amazon, provide new value for our customers, and reduce costs to drive the holistic business flywheel. The Return and Recommerce team is looking for an Economist intern with time series forecasting skills to join our cross-domain group of economists, applied scientists, and business intelligence engineers. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets, and train and deploy time series forecasting solutions at scale. Knowledge of time-series forecasting as well as basic familiarity with either Python or R is necessary. Experience in Bayesian modelling or geospatial forecasting would be a plus. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. Roughly 85% of previous cohorts have converted to full time economist employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com.
Economist, International Seller Service
US, VA, Arlington
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company. About the team The International Seller Services (ISS) Economics team is a dynamic group at the forefront of shaping Amazon's global seller ecosystem. As part of ISS, we drive innovation and growth through sophisticated economic analysis and data-driven insights. Our mission is critical: we're transforming how Amazon empowers millions of international sellers to succeed in the digital marketplace. Our team stands at the intersection of innovative technology and practical business solutions. We're leading Amazon's transformation in seller services through work with Large Language Models (LLMs) and generative AI, while tackling fundamental questions about seller growth, marketplace dynamics, and operational efficiency. What sets us apart is our unique blend of rigorous economic methodology and practical business impact. We're not just analyzing data – we're building the frameworks and measurement systems that will define the future of Amazon's seller services. Whether we're optimizing the seller journey, evaluating new technologies, or designing innovative service models, our team transforms complex economic challenges into actionable insights that drive real-world results. Join us in shaping how millions of businesses worldwide succeed on Amazon's marketplace, while working on problems that combine economic theory, advanced analytics, and innovative technology.
Intern - Economics, WW Returns & ReCommerce
US, WA, Bellevue
The Returns Economics Intelligence team brings together economists, data scientists, data analysts, and business intelligence engineers to deliver innovative research and products that discover and surface returns-influencing behavior, trends and their root causes. We leverage a range of scientific approaches such as causal modeling, structural and choice modeling, time series, ML, and optimization models to yield tangible insights targeted at reducing the cost of returns and concessions without slowing down the Amazon flywheel. We are looking for a detail-oriented, organized and responsible Economist intern with strong skills in time series and macroeconomic modeling. We are a new team at Amazon and this is a great opportunity to be on the leading edge. Roughly 85% of interns from previous cohorts have converted to full time economist employment at Amazon. If you are interested, please apply and send your CV to our mailing list at econ-internship@amazon.com.
Intern - Economics, Amazon Health Services
US, WA, Seattle
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets. Some knowledge of econometrics, as well as basic familiarity with Python is necessary, and experience with SQL and UNIX would be a plus. This position is focused on forecasting and financial modeling. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis at Internet speed collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. Roughly 85% of previous cohorts have converted to full time economist employment at Amazon. If you are interested, please send your CV to our mailing list at: econ-internship@amazon.com.
Economist Manager, CBA
US, WA, Seattle
Amazon.com is seeking a Manager to lead a science team within Customer Forecasting and Valuation (CFV). We own a set of primary decision metrics at Amazon, leveraging causal machine-learning models to predict the long-term impact of customer actions. These metrics drive several investment and launch decisions across Amazon. This fast-paced, cross-disciplinary team of economists and scientists leverages advanced machine learning, statistics, and economics to solve complex problems like measuring the long-term causal effects of Amazon initiatives. CFV is part of the Customer Behavior Analytics (CBA) organization, which is responsible for developing the architecture, design, and implementation of tools used to understand customer behavior and value generation across the company's Retail business. As a manager within CFV, you will lead and collaborate with Applied Scientists, Economists, and Data Scientists to work backwards from customer needs and translate product ideas into concrete deliverables. This will involve inventing scalable causal measurement solutions that provide highly accurate and actionable insights, and drive improvement in key customer lifetime value metrics. You will interface directly with product owners, senior scientists/economists, and business leadership to create multi-year research and product agendas that drive step-change growth. Working with massive datasets spanning billions of customer transactions, you will partner closely with a dedicated engineering team to uncover insights that propel Amazon's Retail business forward. The role will also be an important collaborator with other science teams at CBA and Stores. The ideal candidate will have experience with machine learning models, causal inference, and a strong background in applied science, economics, and engineering. You should also possess creativity, curiosity, and excellent judgment to thrive in an environment of ambiguity. If you are seeking an opportunity to drive innovation, solve real-world problems using advanced analytics, and grow your career over time, this role on Amazon's industry-leading CBA team may be the perfect fit.
Economist II, AWS Central Economics and Science
US, WA, Seattle
We are hiring an Economist to work on understanding and accelerating AWS customer growth. This will involve generating insights on customer growth on AWS, deriving specific policy recommendations to accelerate growth, and planning and executing experiments and/or rigorous quasi-experimental analyses to test out these recommendations. Key job responsibilities This role with interface with product owners, scientists/economists, and leadership to create and execute research agendas that drive step change growth for the business. The role will also be an important collaborator with other science teams at AWS. A day in the life Our team takes big swings and works on hard cross organizational problems where the optimal success rate is not 100%. We also ask people to grow their skills and stretch and make sure we do it in a supportive and fun environment. It’s about empirically measured impact, advancement, and fun on our team. We work hard during work hours but we also don’t encourage working at nights or on weekends except in very rare, high stakes cases. Burn out isn’t a successful long run strategy. Because we invest in the long run success of our group it’s important to have hobbies, relax and then come to work refreshed, and excited. It makes for bigger impact and faster skill accrual and thus career advancement. About the team Our group is technically rigorous and encourages ongoing academic conference participation and publication. Our leaders are here for you and to enable you to be successful. We believe in being servant leaders focused on influence: good data work has little value if it doesn’t translate into actionable insights that are rolled out and impact the real economy. We are communication centric since being able to explain what we do ensures high success rates and lowers administrative churn. Also: we laugh a lot. If it’s not fun, what’s the point?
Economist II, Selling Partner Growth
US, VA, Arlington
Join us in the evolution of Amazon’s Seller business! The Selling Partner Growth organization is the growth and development engine for our Store. Partnering with business, product, and engineering, we catalyze SP growth with comprehensive and accurate data, unique insights, and actionable recommendations and collaborate with WW SP facing teams to drive adoption and create feedback loops. We strongly believe that any motivated SP should be able to grow their businesses and reach their full potential supported by Amazon tools and resources. We are looking for an Economist II to identify data-driven insight and opportunities to improve our SP growth strategy and drive new seller success. As a successful economist on our talented team of scientists and economists, you will solve complex problems to identify actionable insights, and collaborate with engineering, research, and business teams for future innovation. You need to have solid foundation in econometrics and the ability to connect science with business to address specific business questions. We prefer candidates with strong causal background. You are an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication. You will continue to contribute to the economic and research community, by working with economists and scientists across Amazon, as well as collaborating with academic researchers and publishing papers (www.aboutamazon.com/research). Key job responsibilities As an Economist II in the team, you will: - Connect economics with business problems and leverage domain expertise to generate data-driven insights and actionable recommendations - Communicate scientific findings to both technical and non-technical audience to drive for understanding - Work with our engineering partners to build scientific products - Involve and contribute to the broader internal & external scientific community
Economist Manager, AWS Central Economics and Science
US, NY, New York
We are hiring a manager for a cross-functional team that builds ML-based products to help AWS sellers understand customers and optimize sales strategies. This manager will be an important member of the AWS Central Economics and Science team and help set the science and product direction for their team and, by extension, a large part of the org due to within-org collaboration. Specifically, we’re looking for someone to help define a growth- and business-focused vision for the team. An ideal candidate will think big and understands how to use science to drive measurable incremental business impact by taking insights all the way through to actions that manifest in the real economy. This will be a great opportunity to utilize both causal/econ and ML chops. Someone who has worked on embedded teams or on central science teams with policy implementation involvement is ideal. This role lends itself to increased scope and career growth over time. Key job responsibilities This role with interface directly with product owners, scientists/economists, and leadership to create multi-year research and product agendas that drive step change growth for the business. The role will also be an important collaborator with other science teams at AWS. A day in the life Our team takes big swings and works on hard cross organizational problems where the optimal success rate is not 100%. We also ask people to grow their skills and stretch and make sure we do it in a supportive and fun environment. It’s about empirically measured impact, advancement, and fun on our team. We work hard during work hours but we also don’t encourage working at nights or on weekends except in very rare, high stakes cases. Burn out isn’t a successful long run strategy. Because we invest in the long run success of our group it’s important to have hobbies, relax and then come to work refreshed and excited. It makes for bigger impact, faster skill accrual and thus career advancement. About the team Our group is technically rigorous and encourages ongoing academic conference participation and publication. Our leaders are here for you and to enable you to be successful. We believe in being servant leaders focused on influence: good data work has little value if it doesn’t translate into actionable insights that are rolled out and impact the real economy. We are communication centric since being able to explain what we do ensures high success rates and lowers administrative churn. Also: we laugh a lot. If it’s not fun, what’s the point?
Economist III, AWS Central Economics and Science
US, WA, Seattle
We are hiring a Senior Economist with the ability to disambiguate very challenging structural problems in two and multi-sided markets. The right hire will be able to dive deep into the data to come up with stylized facts, build reduced form models that motivate structural assumptions, and build to more complex structural models. The main use case will be understanding how the incremental effects of subsidies to a two sided market relate to sales motions characterized by principal agent problems. Key job responsibilities This role with interface directly with product owners, scientists/economists, and leadership to create multi-year research agendas that drive step change growth for the business. This role is important for the development of the strategic direction of the AWS Central Economics and Science team. The role will also be an important collaborator with other science teams at AWS. A day in the life Our team takes big swings and works on hard cross organizational problems where the optimal success rate is not 100%. We also ask people to grow their skills and stretch and make sure we do it in a supportive and fun environment. It’s about empirically measured impact, advancement, and fun on our team. We work hard during work hours but we also don’t encourage working at nights or on weekends except in very rare, high stakes cases. Burn out isn’t a successful long run strategy. Because we invest in the long run success of our group it’s important to have hobbies, relax and then come to work refreshed, and excited. It makes for bigger impact and faster skill accrual and thus career advancement. About the team Our group is technically rigorous and encourages ongoing academic conference participation and publication. Our leaders are here for you and to enable you to be successful. We believe in being servant leaders focused on influence: good data work has little value if it doesn’t translate into actionable insights that are rolled out and impact the real economy. We are communication centric since being able to explain what we do ensures high success rates and lowers administrative churn. Also: we laugh a lot. If it’s not fun, what’s the point?
Senior Economist, Traffic Insights
US, WA, Seattle
We are working back from a mission of explaining and predicting one of the most important inputs to the Amazon business - customer visit data. We are working to model and test our assumptions about what are the customer incentives and what influences customers to chose visiting Amazon. Ultimately we want to understand and predict how many of our customers will interact with Amazon and we want to identify insights that optimize the customer experience. This is a green-field role in an analytics team of economists, science, business intelligence and data engineering bridging between observational measurement and theoretical models. About the team You will be empowered by a large team of experienced software and data engineers that are aligned on the same mission - to measure and explain our customer experience. We lean into the exceptionally talented Economist and Science community in CBA and Stores for consultation, guidance and peer reviews. Our large analytics team is empowered to move fast and gather the data we need to achieve our mission. Our parent organization owns end-to-end data collection systems (Clickstream), experimentation (Weblab) and customer value forecasting (GCCP). We are working across organizational boundaries to identify relevant datasets and are able to curate the vast amount of data we have into meaningful business reporting and analysis.
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