131 Statsmodels Jobs - Page 2

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – AI and DATA – Statistical Modeler-Senior At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. As part of our EY- GDS AI and Data team, we help our clients solve complex business challenges with the help of data and technology. We dive deep into data to extract the greatest value and discover opportunities in key business and functions like Banking, Insurance, Manufacturing, Healthcare, Retail, Manufacturing and Auto, Supply Chain, and Finance. Technical Skills: Statistical Programming Languages: Python, R Libraries & Frameworks: Pandas, NumPy, Scikit-learn, StatsModels, Tidyverse, caret Data Manipulation Tools: SQL, Excel Data Visualization Tools: Matplotlib, Seaborn, ggplot2, Machine Learning Techniques: Supervised and unsupervised learning, model evaluation (cross-validation, ROC curves) 5-7 years of experience in building statistical forecast models for pharma industry Deep understanding of patient flows,treatment journey across both Onc and Non Onc Tas. What We Look For A Team of people with commercial acumen, technical experience and enthusiasm to learn new things in this fast-moving environment What Working At EY Offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you About EY As a global leader in assurance, tax, transaction and advisory services, we’re using the finance products, expertise and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – AI and DATA – Statistical Modeler-Senior At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. As part of our EY- GDS AI and Data team, we help our clients solve complex business challenges with the help of data and technology. We dive deep into data to extract the greatest value and discover opportunities in key business and functions like Banking, Insurance, Manufacturing, Healthcare, Retail, Manufacturing and Auto, Supply Chain, and Finance. Technical Skills: Statistical Programming Languages: Python, R Libraries & Frameworks: Pandas, NumPy, Scikit-learn, StatsModels, Tidyverse, caret Data Manipulation Tools: SQL, Excel Data Visualization Tools: Matplotlib, Seaborn, ggplot2, Machine Learning Techniques: Supervised and unsupervised learning, model evaluation (cross-validation, ROC curves) 5-7 years of experience in building statistical forecast models for pharma industry Deep understanding of patient flows,treatment journey across both Onc and Non Onc Tas. What We Look For A Team of people with commercial acumen, technical experience and enthusiasm to learn new things in this fast-moving environment What Working At EY Offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you About EY As a global leader in assurance, tax, transaction and advisory services, we’re using the finance products, expertise and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – AI and DATA – Statistical Modeler-Senior At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. As part of our EY- GDS AI and Data team, we help our clients solve complex business challenges with the help of data and technology. We dive deep into data to extract the greatest value and discover opportunities in key business and functions like Banking, Insurance, Manufacturing, Healthcare, Retail, Manufacturing and Auto, Supply Chain, and Finance. Technical Skills: Statistical Programming Languages: Python, R Libraries & Frameworks: Pandas, NumPy, Scikit-learn, StatsModels, Tidyverse, caret Data Manipulation Tools: SQL, Excel Data Visualization Tools: Matplotlib, Seaborn, ggplot2, Machine Learning Techniques: Supervised and unsupervised learning, model evaluation (cross-validation, ROC curves) 5-7 years of experience in building statistical forecast models for pharma industry Deep understanding of patient flows,treatment journey across both Onc and Non Onc Tas. What We Look For A Team of people with commercial acumen, technical experience and enthusiasm to learn new things in this fast-moving environment What Working At EY Offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you About EY As a global leader in assurance, tax, transaction and advisory services, we’re using the finance products, expertise and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – AI and DATA – Statistical Modeler-Senior At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. As part of our EY- GDS AI and Data team, we help our clients solve complex business challenges with the help of data and technology. We dive deep into data to extract the greatest value and discover opportunities in key business and functions like Banking, Insurance, Manufacturing, Healthcare, Retail, Manufacturing and Auto, Supply Chain, and Finance. Technical Skills: Statistical Programming Languages: Python, R Libraries & Frameworks: Pandas, NumPy, Scikit-learn, StatsModels, Tidyverse, caret Data Manipulation Tools: SQL, Excel Data Visualization Tools: Matplotlib, Seaborn, ggplot2, Machine Learning Techniques: Supervised and unsupervised learning, model evaluation (cross-validation, ROC curves) 5-7 years of experience in building statistical forecast models for pharma industry Deep understanding of patient flows,treatment journey across both Onc and Non Onc Tas. What We Look For A Team of people with commercial acumen, technical experience and enthusiasm to learn new things in this fast-moving environment What Working At EY Offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you About EY As a global leader in assurance, tax, transaction and advisory services, we’re using the finance products, expertise and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – AI and DATA – Statistical Modeler-Senior At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. As part of our EY- GDS AI and Data team, we help our clients solve complex business challenges with the help of data and technology. We dive deep into data to extract the greatest value and discover opportunities in key business and functions like Banking, Insurance, Manufacturing, Healthcare, Retail, Manufacturing and Auto, Supply Chain, and Finance. Technical Skills: Statistical Programming Languages: Python, R Libraries & Frameworks: Pandas, NumPy, Scikit-learn, StatsModels, Tidyverse, caret Data Manipulation Tools: SQL, Excel Data Visualization Tools: Matplotlib, Seaborn, ggplot2, Machine Learning Techniques: Supervised and unsupervised learning, model evaluation (cross-validation, ROC curves) 5-7 years of experience in building statistical forecast models for pharma industry Deep understanding of patient flows,treatment journey across both Onc and Non Onc Tas. What We Look For A Team of people with commercial acumen, technical experience and enthusiasm to learn new things in this fast-moving environment What Working At EY Offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you About EY As a global leader in assurance, tax, transaction and advisory services, we’re using the finance products, expertise and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – AI and DATA – Statistical Modeler-Senior At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. As part of our EY- GDS AI and Data team, we help our clients solve complex business challenges with the help of data and technology. We dive deep into data to extract the greatest value and discover opportunities in key business and functions like Banking, Insurance, Manufacturing, Healthcare, Retail, Manufacturing and Auto, Supply Chain, and Finance. Technical Skills: Statistical Programming Languages: Python, R Libraries & Frameworks: Pandas, NumPy, Scikit-learn, StatsModels, Tidyverse, caret Data Manipulation Tools: SQL, Excel Data Visualization Tools: Matplotlib, Seaborn, ggplot2, Machine Learning Techniques: Supervised and unsupervised learning, model evaluation (cross-validation, ROC curves) 5-7 years of experience in building statistical forecast models for pharma industry Deep understanding of patient flows,treatment journey across both Onc and Non Onc Tas. What We Look For A Team of people with commercial acumen, technical experience and enthusiasm to learn new things in this fast-moving environment What Working At EY Offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you About EY As a global leader in assurance, tax, transaction and advisory services, we’re using the finance products, expertise and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – AI and DATA – Statistical Modeler-Senior At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. As part of our EY- GDS AI and Data team, we help our clients solve complex business challenges with the help of data and technology. We dive deep into data to extract the greatest value and discover opportunities in key business and functions like Banking, Insurance, Manufacturing, Healthcare, Retail, Manufacturing and Auto, Supply Chain, and Finance. Technical Skills: Statistical Programming Languages: Python, R Libraries & Frameworks: Pandas, NumPy, Scikit-learn, StatsModels, Tidyverse, caret Data Manipulation Tools: SQL, Excel Data Visualization Tools: Matplotlib, Seaborn, ggplot2, Machine Learning Techniques: Supervised and unsupervised learning, model evaluation (cross-validation, ROC curves) 5-7 years of experience in building statistical forecast models for pharma industry Deep understanding of patient flows,treatment journey across both Onc and Non Onc Tas. What We Look For A Team of people with commercial acumen, technical experience and enthusiasm to learn new things in this fast-moving environment What Working At EY Offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you About EY As a global leader in assurance, tax, transaction and advisory services, we’re using the finance products, expertise and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – AI and DATA – Statistical Modeler-Senior At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. As part of our EY- GDS AI and Data team, we help our clients solve complex business challenges with the help of data and technology. We dive deep into data to extract the greatest value and discover opportunities in key business and functions like Banking, Insurance, Manufacturing, Healthcare, Retail, Manufacturing and Auto, Supply Chain, and Finance. Technical Skills: Statistical Programming Languages: Python, R Libraries & Frameworks: Pandas, NumPy, Scikit-learn, StatsModels, Tidyverse, caret Data Manipulation Tools: SQL, Excel Data Visualization Tools: Matplotlib, Seaborn, ggplot2, Machine Learning Techniques: Supervised and unsupervised learning, model evaluation (cross-validation, ROC curves) 5-7 years of experience in building statistical forecast models for pharma industry Deep understanding of patient flows,treatment journey across both Onc and Non Onc Tas. What We Look For A Team of people with commercial acumen, technical experience and enthusiasm to learn new things in this fast-moving environment What Working At EY Offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you About EY As a global leader in assurance, tax, transaction and advisory services, we’re using the finance products, expertise and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – AI and DATA – Statistical Modeler-Senior At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. As part of our EY- GDS AI and Data team, we help our clients solve complex business challenges with the help of data and technology. We dive deep into data to extract the greatest value and discover opportunities in key business and functions like Banking, Insurance, Manufacturing, Healthcare, Retail, Manufacturing and Auto, Supply Chain, and Finance. Technical Skills: Statistical Programming Languages: Python, R Libraries & Frameworks: Pandas, NumPy, Scikit-learn, StatsModels, Tidyverse, caret Data Manipulation Tools: SQL, Excel Data Visualization Tools: Matplotlib, Seaborn, ggplot2, Machine Learning Techniques: Supervised and unsupervised learning, model evaluation (cross-validation, ROC curves) 5-7 years of experience in building statistical forecast models for pharma industry Deep understanding of patient flows,treatment journey across both Onc and Non Onc Tas. What We Look For A Team of people with commercial acumen, technical experience and enthusiasm to learn new things in this fast-moving environment What Working At EY Offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you About EY As a global leader in assurance, tax, transaction and advisory services, we’re using the finance products, expertise and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – AI and DATA – Statistical Modeler-Senior At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. As part of our EY- GDS AI and Data team, we help our clients solve complex business challenges with the help of data and technology. We dive deep into data to extract the greatest value and discover opportunities in key business and functions like Banking, Insurance, Manufacturing, Healthcare, Retail, Manufacturing and Auto, Supply Chain, and Finance. Technical Skills: Statistical Programming Languages: Python, R Libraries & Frameworks: Pandas, NumPy, Scikit-learn, StatsModels, Tidyverse, caret Data Manipulation Tools: SQL, Excel Data Visualization Tools: Matplotlib, Seaborn, ggplot2, Machine Learning Techniques: Supervised and unsupervised learning, model evaluation (cross-validation, ROC curves) 5-7 years of experience in building statistical forecast models for pharma industry Deep understanding of patient flows,treatment journey across both Onc and Non Onc Tas. What We Look For A Team of people with commercial acumen, technical experience and enthusiasm to learn new things in this fast-moving environment What Working At EY Offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you About EY As a global leader in assurance, tax, transaction and advisory services, we’re using the finance products, expertise and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – AI and DATA – Statistical Modeler-Senior At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. As part of our EY- GDS AI and Data team, we help our clients solve complex business challenges with the help of data and technology. We dive deep into data to extract the greatest value and discover opportunities in key business and functions like Banking, Insurance, Manufacturing, Healthcare, Retail, Manufacturing and Auto, Supply Chain, and Finance. Technical Skills: Statistical Programming Languages: Python, R Libraries & Frameworks: Pandas, NumPy, Scikit-learn, StatsModels, Tidyverse, caret Data Manipulation Tools: SQL, Excel Data Visualization Tools: Matplotlib, Seaborn, ggplot2, Machine Learning Techniques: Supervised and unsupervised learning, model evaluation (cross-validation, ROC curves) 5-7 years of experience in building statistical forecast models for pharma industry Deep understanding of patient flows,treatment journey across both Onc and Non Onc Tas. What We Look For A Team of people with commercial acumen, technical experience and enthusiasm to learn new things in this fast-moving environment What Working At EY Offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you About EY As a global leader in assurance, tax, transaction and advisory services, we’re using the finance products, expertise and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

We are building Saulikh, a platform transforming agri-trade with data science and AI. Our goal is to bring trust, transparency, and intelligence to commodity trading at scale. Role Overview We are seeking a Data Scientist to lead data-driven initiatives across trade, pricing, risk, and logistics. The role involves working with real-world datasets, building dashboards, applying ML models, and assisting in the development of prototypes for trust scoring, fraud detection, and forecasting. Key Responsibilities Collect, clean, and preprocess financial, transactional, and behavioral datasets from multiple sources. Design and implement trust/credit scoring algorithms that assess buyer/seller reliability and default risk. Engineer features from trade history, payment timeliness, disputes, cancellations, and external market data. Apply statistical models and machine learning techniques (logistic regression, random forests, gradient boosting, neural networks) to predict trustworthiness. Develop scoring frameworks normalized to a range (e.g., 01000), similar to CIBIL standards. Validate and back-test models against historical data to ensure accuracy, fairness, and stability. Build monitoring pipelines to track score performance, drift, and anomalies in real time. Work with business and product teams to ensure scores align with practical trade and risk management requirements. Document methodologies and communicate insights to technical and non-technical stakeholders. Requirements Bachelors or Masters degree in Computer Science, Statistics, Mathematics, Economics, or a related field. 25 years of experience as a Data Scientist, preferably in credit scoring, risk modeling, or fraud detection. Strong proficiency in Python (pandas, numpy, scikit-learn, statsmodels) or R. Experience with machine learning algorithms such as logistic regression, decision trees, random forests, gradient boosting (XGBoost/LightGBM), and neural networks. Strong SQL skills for handling large datasets; experience with data pipelines and API integrations. Domain knowledge of credit scoring principles, risk assessment, and regulatory considerations . Experience in model validation, back-testing, and ensuring fairness and interpretability. Excellent analytical and problem-solving skills with attention to detail. Strong communication skills for presenting findings to technical and business stakeholders. The interested candidates may apply here. Show more Show less

About GreedyGame GreedyGame is a leading ad-tech company that's been driving app growth and monetization. We’ve built a sustainable and profitable business for over 7 years without chasing vanity metrics and successfully completed our 0→1 journey, we’re now scaling rapidly (1→10 phase) As a Google Publishing Partner, we serve 100M+ daily ad impressions and support 5,000+ apps and games worldwide—delivering up to 75% revenue uplift Trusted by brands like Amazon, Dream11, MPL, Sharechat, Treebo, Mobikwik, and 1000+ publishers across 20+ countries. We are looking for a Data Scientist who can turn this data into foresight building models that predict campaign outcomes, forecast publisher revenue, and power decision-making at scale. Responsibilities- Revenue Forecasting: Build predictive models to estimate publisher revenue streams, fill rates, and eCPM across different ad networks and geographies. User Behavior Prediction: Analyze in-app user journeys and predict churn, retention, and engagement to help publishers personalize experiences. Ad Performance Modeling: Develop CTR and conversion rate prediction models to optimize bidding strategies and ad placements. Inventory Forecasting: Forecast ad inventory availability and demand to help sales and publisher teams plan better. Campaign Optimization: Work with account managers and product teams to provide real-time insights on campaign pacing, under-delivery risks, and performance anomalies. Experimentation: Design and run experiments (A/B/n tests) to evaluate new ad formats, placements, and targeting algorithms. Data Products: Partner with engineering to embed forecasting models into GreedyGame’s platform, enabling self-serve insights for publishers and advertisers. Requirements - 2–4 years of hands-on experience in predictive analytics, time series forecasting, or applied ML. Strong proficiency in Python (Pandas, NumPy, Scikit-learn, Statsmodels) and SQL. Familiarity with MLOps practices (model deployment, monitoring, retraining). Solid understanding of statistical inference, experiment design, and causal analysis. Knowledge of real-time prediction pipelines (Kafka, Spark) Nice to Have Exposure to adtech, gaming analytics, or digital marketing intelligence. Familiarity with retrieval-augmented generation (RAG) or fine-tuning for domain-specific insights. Experience with cloud AI/ML services (GCP Vertex AI, AWS Sagemaker, Azure ML). Exposure to GenAI and LLMs for applied use cases (e.g., automated report generation, text summarization of campaign insights, anomaly explanation, or predictive storytelling). 🎁 Why GreedyGame? Opportunity to work on products used by millions – see: Pubscale Ownership from Day 1 – shape architecture, strategy, and key decisions Learning stipend for books, courses, and conferences (we love curious minds!) internal blogs Flexible hybrid work setup – split time between our Bangalore HQ and remote work Comprehensive benefits – health insurance, PTO, parental leave, and more A high-growth, inclusive, and engineering-led culture that supports experimentation and impact Skills: forecasting,prediction,python,genai,mlops,data,a/b testing

Job ID: 270918 Technology - Backend Hybrid Bangalore, Karnataka, India 3 - 6 years About GreedyGame GreedyGame is a leading ad-tech company that's been driving app growth and monetization. We’ve built a sustainable and profitable business for over 7 years without chasing vanity metrics and successfully completed our 0 1 journey, we’re now scaling rapidly (1 10 phase) As a Google Publishing Partner , we serve 100M+ daily ad impressions and support 5,000+ apps and games worldwide—delivering up to 75% revenue uplift Trusted by brands like Amazon, Dream11, MPL, Sharechat, Treebo, Mobikwik , and 1000+ publishers across 20+ countries. We are looking for a Data Scientist who can turn this data into foresight building models that predict campaign outcomes, forecast publisher revenue, and power decision-making at scale. Responsibilities- Revenue Forecasting : Build predictive models to estimate publisher revenue streams, fill rates, and eCPM across different ad networks and geographies. User Behavior Prediction : Analyze in-app user journeys and predict churn, retention, and engagement to help publishers personalize experiences. Ad Performance Modeling : Develop CTR and conversion rate prediction models to optimize bidding strategies and ad placements. Inventory Forecasting : Forecast ad inventory availability and demand to help sales and publisher teams plan better. Campaign Optimization : Work with account managers and product teams to provide real-time insights on campaign pacing, under-delivery risks, and performance anomalies. Experimentation : Design and run experiments (A/B/n tests) to evaluate new ad formats, placements, and targeting algorithms. Data Products : Partner with engineering to embed forecasting models into GreedyGame’s platform, enabling self-serve insights for publishers and advertisers. Requirements - 2–4 years of hands-on experience in predictive analytics , time series forecasting, or applied ML. Strong proficiency in Python (Pandas, NumPy, Scikit-learn, Statsmodels) and SQL. Familiarity with MLOps practices (model deployment, monitoring, retraining). Solid understanding of statistical inference, experiment design, and causal analysis. Knowledge of real-time prediction pipelines (Kafka, Spark) Nice to Have Exposure to adtech, gaming analytics, or digital marketing intelligence. Familiarity with retrieval-augmented generation (RAG) or fine-tuning for domain-specific insights. Experience with cloud AI/ML services (GCP Vertex AI, AWS Sagemaker, Azure ML). Exposure to GenAI and LLMs for applied use cases (e.g., automated report generation, text summarization of campaign insights, anomaly explanation, or predictive storytelling). Why GreedyGame? Opportunity to work on products used by millions – see: Pubscale Ownership from Day 1 – shape architecture, strategy, and key decisions Learning stipend for books, courses, and conferences (we love curious minds!) internal blogs Flexible hybrid work setup – split time between our Bangalore HQ and remote work Comprehensive benefits – health insurance, PTO, parental leave, and more A high-growth, inclusive, and engineering-led culture that supports experimentation and impact Workplace Type Hybrid Employment Type Full-Time Experience Level Mid-Senior-Level Work Experience (years) 3 - 6 years Skills Forecasting Prediction Python Genai Mlops Data A/B Testing

We are building Saulikh, a platform transforming agri-trade with data science and AI. Our goal is to bring trust, transparency, and intelligence to commodity trading at scale. Role Overview We are seeking a Data Scientist to lead data-driven initiatives across trade, pricing, risk, and logistics. The role involves working with real-world datasets, building dashboards, applying ML models, and assisting in the development of prototypes for trust scoring, fraud detection, and forecasting. Key Responsibilities Collect, clean, and preprocess financial, transactional, and behavioral datasets from multiple sources. Design and implement trust/credit scoring algorithms that assess buyer/seller reliability and default risk. Engineer features from trade history, payment timeliness, disputes, cancellations, and external market data. Apply statistical models and machine learning techniques (logistic regression, random forests, gradient boosting, neural networks) to predict trustworthiness. Develop scoring frameworks normalized to a range (e.g., 0–1000), similar to CIBIL standards. Validate and back-test models against historical data to ensure accuracy, fairness, and stability. Build monitoring pipelines to track score performance, drift, and anomalies in real time. Work with business and product teams to ensure scores align with practical trade and risk management requirements. Document methodologies and communicate insights to technical and non-technical stakeholders. Requirements Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Economics, or a related field. 2–5 years of experience as a Data Scientist, preferably in credit scoring, risk modeling, or fraud detection. Strong proficiency in Python (pandas, numpy, scikit-learn, statsmodels) or R. Experience with machine learning algorithms such as logistic regression, decision trees, random forests, gradient boosting (XGBoost/LightGBM), and neural networks. Strong SQL skills for handling large datasets; experience with data pipelines and API integrations. Domain knowledge of credit scoring principles, risk assessment, and regulatory considerations . Experience in model validation, back-testing, and ensuring fairness and interpretability. Excellent analytical and problem-solving skills with attention to detail. Strong communication skills for presenting findings to technical and business stakeholders. The interested candidates may apply here.

Job Description At American Express, our culture is built on a 175-year history of innovation, sharedand Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. As part of Team Amex, you'll experience this powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express. How will you make an impact in this role This Position is in GSG Advanced Analytics team as part of GSG MIS COE, is looking for full time candidates as Data Science Analysts. The Advanced Analytics team works across multiple Data Science/Machine Learning portfolio of projects across GSG organization across multiple areas of Servicing. Understand the overall business perspective and help conceptualize the business problem into a Data Science/ML roadmap Have a research bend of mind and read/engage/apply new techniques and algorithms in the field to generate efficiencies/process improvements. Rigorous testing of algorithms as per business norms and delivering significant working leverage over status quo and generate value for the business. Capability of writing, debugging and compiling codes in multiple Machine Learning environment and understanding of Python stack is necessary Research focus on problem solving through NLP(Natural Language Processing) is critical. Clear application on performance testing and validation framework of machine learning models Understand and deploy mathematical foundations of cutting edge NLP techniques on varied sources of data Willingness to derive insights from terabyte sized data and capability to design scalable solutions is paramount Minimum Qualifications Proven experience of applying using Machine Learning techniques like Regression, Classification, Supervised or Unsupervised Recommenders, Deep Learning etc. Ability to work in cross functional teams Excellent data wrangling and visualization skills Hands on knowledge of SQL is expected A research mindset with a zeal to experiment new algorithms is expected Preferred Qualifications: Master's in a quantitative field (e.g., Finance, Engineering, Mathematics, Statistics Computer Science or Economics) from a top institute. A set of high impact research papers on applied NLP/ Deep Learning/ GenAI Prior experience working with Transformers/LSTMs/CNNs preferred Working knowledge of finetuning Large Language Models(LLMs) is a plus Deep knowledge of Statistics and Mathematics and ability to dissect problems from the first principle. Exposure to fields like Linear Algebra, Bayesian Statistics, Group theory is desirable Complete grip on Python environment and libraries (pandas, numpy, nltk, statsmodels, gensim, pyspark, spacy, transformers), Deep learning expertise is preferred and any of Tensorflow/Torch is preferred. We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally: Competitive base salaries Bonus incentives Support for financial-well-being and retirement Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need Generous paid parental leave policies (depending on your location) Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) Free and confidential counseling support through our Healthy Minds program Career development and training opportunities American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.

At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. As part of Team Amex, you'll experience this powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express. How will you make an impact in this role? This Position is in GSG Advanced Analytics team as part of GSG MIS COE, is looking for full time candidates as Data Science Analysts. The Advanced Analytics team works across multiple Data Science/Machine Learning portfolio of projects across GSG organization across multiple areas of Servicing. Understand the overall business perspective and help conceptualize the business problem into a Data Science/ML roadmap Have a research bend of mind and read/engage/apply new techniques and algorithms in the field to generate efficiencies/process improvements. Rigorous testing of algorithms as per business norms and delivering significant working leverage over status quo and generate value for the business. Capability of writing, debugging and compiling codes in multiple Machine Learning environment and understanding of Python stack is necessary Research focus on problem solving through NLP(Natural Language Processing) is critical. Clear application on performance testing and validation framework of machine learning models Understand and deploy mathematical foundations of cutting edge NLP techniques on varied sources of data Willingness to derive insights from terabyte sized data and capability to design scalable solutions is paramount Minimum Qualifications Proven experience of applying using Machine Learning techniques like Regression, Classification, Supervised or Unsupervised Recommenders, Deep Learning etc. Ability to work in cross functional teams Excellent data wrangling and visualization skills Hands on knowledge of SQL is expected A research mindset with a zeal to experiment new algorithms is expected Preferred Qualifications: Master’s in a quantitative field (e.g., Finance, Engineering, Mathematics, Statistics Computer Science or Economics) from a top institute. A set of high impact research papers on applied NLP/ Deep Learning/ GenAI Prior experience working with Transformers/LSTMs/CNNs preferred Working knowledge of finetuning Large Language Models(LLMs) is a plus Deep knowledge of Statistics and Mathematics and ability to dissect problems from the first principle. Exposure to fields like Linear Algebra, Bayesian Statistics, Group theory is desirable Complete grip on Python environment and libraries (pandas, numpy, nltk, statsmodels, gensim, pyspark, spacy, transformers), Deep learning expertise is preferred and any of Tensorflow/Torch is preferred. We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally: Competitive base salaries Bonus incentives Support for financial-well-being and retirement Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need Generous paid parental leave policies (depending on your location) Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) Free and confidential counseling support through our Healthy Minds program Career development and training opportunities American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.

We are seeking an exceptional and highly motivated Lead Data Scientist with a experience in Data Science, Computer Science, Applied Mathematics, Statistics, or a closely related quantitative field, to spearhead the design, development, and deployment of an automotive OEM’s next-generation Intelligent Forecast Application. This pivotal role will leverage cutting-edge machine learning, deep learning, and statistical modeling techniques to build a robust, scalable, and accurate forecasting system crucial for strategic decision-making across the automotive value chain, including demand planning, production scheduling, inventory optimization, predictive maintenance, and new product introduction. The successful candidate will be a recognized expert in advanced forecasting methodologies, possess a strong foundation in data engineering and MLOps principles, and demonstrate a proven ability to translate complex research into tangible, production-ready applications within a dynamic industrial environment. This role demands not only deep technical expertise but also a visionary approach to leveraging data and AI to drive significant business impact for a leading automotive OEM. Role & Responsibilities: Strategic Leadership & Application Design: Lead the end-to-end design and architecture of the Intelligent Forecast Application, defining its capabilities, modularity, and integration points with existing enterprise systems (e.g., ERP, SCM, CRM). Develop a strategic roadmap for forecasting capabilities, identifying opportunities for innovation and the adoption of emerging AI/ML techniques (e.g., generative AI for scenario planning, reinforcement learning for dynamic optimization). Translate complex business requirements and automotive industry challenges into well-defined data science problems and technical specifications. Advanced Model Development & Research: Design, develop, and validate highly accurate and robust forecasting models using a variety of advanced techniques, including: Time Series Analysis: ARIMA, SARIMA, Prophet, Exponential Smoothing, State-space models. Machine Learning: Gradient Boosting (XGBoost, LightGBM), Random Forests, Support Vector Machines. Deep Learning: LSTMs, GRUs, Transformers, and other neural network architectures for complex sequential data. Probabilistic Forecasting: Quantile regression, Bayesian methods to capture uncertainty. Hierarchical & Grouped Forecasting: Managing forecasts across multiple product hierarchies, regions, and dealerships. Incorporate diverse data sources, including historical sales, market trends, economic indicators, competitor data, internal operational data (e.g., production schedules, supply chain disruptions), external events, and unstructured data. Conduct extensive exploratory data analysis (EDA) to identify patterns, anomalies, and key features influencing automotive forecasts. Stay abreast of the latest academic research and industry advancements in forecasting, machine learning, and AI, actively evaluating and advocating for their practical application within the OEM. Application Development & Deployment (MLOps): Architect and implement scalable data pipelines for ingestion, cleaning, transformation, and feature engineering of large, complex automotive datasets. Develop robust and efficient code for model training, inference, and deployment within a production environment. Implement MLOps best practices for model versioning, monitoring, retraining, and performance management to ensure the continuous accuracy and reliability of the forecasting application. Collaborate closely with Data Engineering, Software Development, and IT Operations teams to ensure seamless integration, deployment, and maintenance of the application. Performance Evaluation & Optimization: Define and implement rigorous evaluation metrics for forecasting accuracy (e.g., MAE, RMSE, MAPE, sMAPE, wMAPE, Pinball Loss) and business impact. Perform A/B testing and comparative analyses of different models and approaches to continuously improve forecasting performance. Identify and mitigate sources of bias and uncertainty in forecasting models. Collaboration & Mentorship: Work cross-functionally with various business units (e.g., Sales, Marketing, Supply Chain, Manufacturing, Finance, Product Development) to understand their forecasting needs and integrate solutions. Communicate complex technical concepts and model insights clearly and concisely to both technical and non-technical stakeholders. Provide technical leadership and mentorship to junior data scientists and engineers, fostering a culture of innovation and continuous learning. Potentially contribute to intellectual property (patents) and present findings at internal and external conferences. Requirements Qualifications: Education: Data Science, Computer Science, Statistics, Applied Mathematics, Operations Research, or a closely related quantitative field. Location : Jaipur / Kolkata / Bangalore Experience: 5+ years of hands-on experience in a Data Scientist or Machine Learning Engineer role, with a significant focus on developing and deploying advanced forecasting solutions in a production environment. Demonstrated experience designing and developing intelligent applications, not just isolated models. Experience in the automotive industry or a similar complex manufacturing/supply chain environment is highly desirable. Technical Skills: Expert proficiency in Python (Numpy, Pandas, Scikit-learn, Statsmodels) and/or R. Strong proficiency in SQL. Machine Learning/Deep Learning Frameworks: Extensive experience with TensorFlow, PyTorch, Keras, or similar deep learning libraries. Forecasting Specific Libraries: Proficiency with forecasting libraries like Prophet, Statsmodels, or specialized time series packages. Data Warehousing & Big Data Technologies: Experience with distributed computing frameworks (e.g., Apache Spark, Hadoop) and data storage solutions (e.g., Snowflake, Databricks, S3, ADLS). Cloud Platforms: Hands-on experience with at least one major cloud provider (Azure, AWS, GCP) for data science and ML deployments. MLOps: Understanding and practical experience with MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes, CI/CD pipelines). Data Visualization: Proficiency with tools like Tableau, Power BI, or similar for creating compelling data stories and dashboards. Analytical Prowess: Deep understanding of statistical inference, experimental design, causal inference, and the mathematical foundations of machine learning algorithms. Problem Solving: Proven ability to analyze complex, ambiguous problems, break them down into manageable components, and devise innovative solutions. Preferred Qualifications Publications in top-tier conferences or journals related to forecasting, time series analysis, or applied machine learning. Experience with real-time forecasting systems or streaming data analytics. Familiarity with specific automotive data types (e.g., telematics, vehicle sensor data, dealership data, market sentiment). Experience with distributed version control systems (e.g., Git). Knowledge of agile development methodologies. Soft Skills Exceptional Communication: Ability to articulate complex technical concepts and insights to a diverse audience, including senior management and non-technical stakeholders. Collaboration: Strong interpersonal skills and a proven ability to work effectively within cross-functional teams. Intellectual Curiosity & Proactiveness: A passion for continuous learning, staying ahead of industry trends, and proactively identifying opportunities for improvement. Strategic Thinking: Ability to see the big picture and align technical solutions with overall business objectives. Mentorship: Desire and ability to guide and develop less experienced team members. Resilience & Adaptability: Thrive in a fast-paced, evolving environment with complex challenges. Signs You May Be a Great Fit Impact: Play a pivotal role in shaping a rapidly growing venture studio. Culture: Thrive in a collaborative, innovative environment that values creativity and ownership. Growth: Access professional development opportunities and mentorship. Benefits: Competitive salary, health/wellness packages, and flexible work options.

Company Description Blend is building a scalable Media Mix Optimization (MMO) solution designed to help clients maximize the impact of their marketing investments. We are seeking a Data Scientist with strong expertise in media mix modeling, statistical modeling, and interactive application development to join our advanced analytics team. This role goes beyond model building — you will design, implement, and productionize end-to-end solutions that integrate statistical rigor with business impact. The ideal candidate will have deep knowledge of marketing analytics, advanced Python skills, and hands-on experience with Streamlit or similar frameworks for interactive data applications. You will be central in creating robust pipelines, experimentation frameworks, and client-facing tools that directly inform media allocation decisions. Job Description Project Overview: Media Mix Optimization (MMO) Our MMO platform is an in-house initiative designed to empower clients with data-driven decision-making in marketing strategy. By applying Bayesian and frequentist approaches to media mix modeling, we are able to quantify channel-level ROI, measure incrementality, and simulate outcomes under varying spend scenarios. Key Components Of The Project Include Data Integration: Combining client first-party, third-party, and campaign-level data across digital, offline, and emerging channels into a unified modeling framework. Model Development: Building and validating media mix models (MMM) using advanced statistical and machine learning techniques such as hierarchical Bayesian regression, regularized regression (Ridge/Lasso), and time-series modeling. Scenario Simulation: Enabling stakeholders to forecast outcomes under different budget allocations through simulation and optimization algorithms. Deployment & Visualization: Using Streamlit to build interactive, client-facing dashboards for model exploration, scenario planning, and actionable recommendation delivery. Scalability: Engineering the system to support multiple clients across industries with varying data volumes, refresh cycles, and modeling complexities. Responsibilities Develop, validate, and maintain media mix models to evaluate cross-channel marketing effectiveness and return on investment. Engineer and optimize end-to-end data pipelines for ingesting, cleaning, and structuring large, heterogeneous datasets from multiple marketing and business sources. Design, build, and deploy Streamlit-based interactive dashboards and applications for scenario testing, optimization, and reporting. Conduct exploratory data analysis (EDA) and advanced feature engineering to identify drivers of performance. Apply Bayesian methods, regularization, and time-series analysis to improve model accuracy, stability, and interpretability. Implement optimization and scenario-planning algorithms to recommend budget allocation strategies that maximize business outcomes. Collaborate closely with product, engineering, and client teams to align technical solutions with business objectives. Present insights and recommendations to senior stakeholders in both technical and non- technical language. Stay current with emerging tools, techniques, and best practices in media mix modeling, causal inference, and marketing science. Qualifications Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Applied Mathematics, or related field. Proven hands-on experience in media mix modeling, marketing analytics, or econometrics. Strong proficiency in Python and key data science libraries (pandas, NumPy, scikit-learn, statsmodels, PyMC or similar Bayesian frameworks). Experience with Streamlit or equivalent frameworks (Dash, Shiny) for building data- driven applications. Proficiency in SQL for querying, joining, and optimizing large-scale datasets. Solid foundation in statistical modeling, regression techniques, and machine learning. Strong problem-solving skills with the ability to structure ambiguous business problems into data-driven solutions. Excellent verbal and written communication skills to translate technical outputs into business decisions. Preferred Qualifications Experience with Bayesian hierarchical models, time-series decomposition, and marketing attribution approaches. Familiarity with cloud-based platforms (AWS, GCP, Azure) for data processing, model training, and deployment. Experience with data visualization tools beyond Streamlit (Tableau, Power BI, D3.js, Plotly). Exposure to big data ecosystems (Spark, Hadoop) for large-scale data processing. Knowledge of causal inference techniques (propensity scoring, uplift modeling, geo- experiments).

At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. As part of Team Amex, you'll experience this powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express. How will you make an impact in this role? This Position is in GSG Advanced Analytics team as part of GSG MIS COE, is looking for full time candidates as Data Science Analysts. The Advanced Analytics team works across multiple Data Science/Machine Learning portfolio of projects across GSG organization across multiple areas of Servicing. Understand the overall business perspective and help conceptualize the business problem into a Data Science/ML roadmap Have a research bend of mind and read/engage/apply new techniques and algorithms in the field to generate efficiencies/process improvements. Rigorous testing of algorithms as per business norms and delivering significant working leverage over status quo and generate value for the business. Capability of writing, debugging and compiling codes in multiple Machine Learning environment and understanding of Python stack is necessary Research focus on problem solving through NLP(Natural Language Processing) is critical. Clear application on performance testing and validation framework of machine learning models Understand and deploy mathematical foundations of cutting edge NLP techniques on varied sources of data Willingness to derive insights from terabyte sized data and capability to design scalable solutions is paramount Minimum Qualifications Proven experience of applying using Machine Learning techniques like Regression, Classification, Supervised or Unsupervised Recommenders, Deep Learning etc. Ability to work in cross functional teams Excellent data wrangling and visualization skills Hands on knowledge of SQL is expected A research mindset with a zeal to experiment new algorithms is expected Preferred Qualifications: Master’s in a quantitative field (e.g., Finance, Engineering, Mathematics, Statistics Computer Science or Economics) from a top institute. A set of high impact research papers on applied NLP/ Deep Learning/ GenAI Prior experience working with Transformers/LSTMs/CNNs preferred Working knowledge of finetuning Large Language Models(LLMs) is a plus Deep knowledge of Statistics and Mathematics and ability to dissect problems from the first principle. Exposure to fields like Linear Algebra, Bayesian Statistics, Group theory is desirable Complete grip on Python environment and libraries (pandas, numpy, nltk, statsmodels, gensim, pyspark, spacy, transformers), Deep learning expertise is preferred and any of Tensorflow/Torch is preferred. We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally: Competitive base salaries Bonus incentives Support for financial-well-being and retirement Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need Generous paid parental leave policies (depending on your location) Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) Free and confidential counseling support through our Healthy Minds program Career development and training opportunities American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.

Job Title: Quantitative Trader (Forex) Location: Indore, MP, India (Onsite only - Work from office) Experience Level: 3–5 years Employment Type: Full-time Role Overview Tecnomi, an innovative IT firm, is hiring a skilled Quantitative Trader to drive profitable, systematic forex strategies. You'll collaborate with the CTO, project owner, and dev team to develop, deploy, and refine live trading models that deliver real-world results. This onsite role offers hands-on involvement in cutting-edge AI integrations, risk management, and data-driven decision-making in a fast-paced, collaborative environment focused on long-term innovation and platform growth. Key Responsibilities Strategy Development & Execution: Design, test, and deploy quantitative trading strategies leveraging price data, volatility, sentiment indicators, and macroeconomic factors for live forex markets. Modeling & Backtesting: Create reliable forecasting models (e.g., time-series, LSTM/Transformer hybrids) with thorough backtesting, forward-testing, and optimization for profitability and robustness. Risk Management: Build and integrate risk controls (e.g., Value-at-Risk, drawdown limits, position sizing) to ensure compliance and minimize losses in volatile conditions. Data Integration: Source, clean, and analyze diverse data feeds (e.g., news APIs, order books, economic calendars) to enhance model inputs and trading signals. Mentorship & Knowledge Sharing: Mentor non-technical team members (including the project owner) on forex basics, quantitative trading concepts, and strategy insights through regular sessions. Collaboration & Documentation: Partner with developers to embed models into production systems; maintain detailed documentation of strategies, assumptions, and performance metrics for transparency and iteration. Required Qualifications 3–5 years of hands-on experience in quantitative trading or systematic strategy development, ideally in forex or similar markets. Proven track record with backtesting tools, statistical validation, and live strategy deployment. Deep knowledge of FX market dynamics, macroeconomic influences, and risk modeling. Strong communication and teaching abilities to guide non-experts effectively. Bachelor’s or Master’s degree in Quantitative Finance, Mathematics, Statistics, or a related field. Verifiable 3-year portfolio of past strategies, backtests, performance reports, or live trading results. Preferred Skills Experience trading multiple forex pairs or cross-asset strategies. Proficiency in Python or R (e.g., pandas, NumPy, statsmodels, scikit-learn) for rapid prototyping. Familiarity with Indian regulatory frameworks (e.g., RBI/FEMA). Exposure to platforms like QuantConnect, TradingView, or MLflow for strategy automation.

Ready to build the future with AI At Genpact, we don&rsquot just keep up with technology&mdashwe set the pace. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos AI Gigafactory, our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what&rsquos possible, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook. Inviting applications for the role of Manager, Data Scientist We are looking for a highly motivated and technically proficient Senior Data Scientist with deep expertise in time series forecasting, machine learning, natural language processing (NLP), and Python programming. This role is critical to enhancing our forecasting capabilities, driving product segmentation strategies, and supporting data-driven decision-making. The candidate will work closely with cross-functional teams including data engineers, analysts, and project managers to develop, test, and deploy scalable forecasting models and analytical solutions in a cloud-based environment. Responsibilities 1. Forecasting & Model Development . Design, develop, and implement advanced time series forecasting models (e.g., ARIMA, Prophet, LSTM, XGBoost, etc.) tailored to different product categories and business needs. . Evaluate and improve forecast accuracy by establishing robust metrics and conducting regular performance assessments throughout the sales cycle. . Run what-if scenarios and simulations to assess the impact of various business conditions on forecast outcomes. 2. Segmentation & Clustering . Collaborate with the Senior Data Scientist to perform segmentation and clustering of product identifiers using unsupervised learning techniques (e.g., K-means, DBSCAN, hierarchical clustering). . Analyze product behavior patterns to identify slow- and fast-moving items, and generate actionable insights for inventory and sales planning. 3. Data Extraction & Feature Engineering . Extract, clean, and transform data from multiple source systems (e.g., SQL databases, APIs, cloud storage) to support modeling and analysis. . Engineer relevant features and variables to enhance model performance and interpretability. 4. Model Evaluation & Deployment . Conduct comparative analysis of forecasting methods across different segments, tuning parameters and optimizing performance. . Work in close coordination with Data Engineers and cloud platform teams to ensure seamless deployment of models into production environments (e.g., AWS, Azure, GCP). . Monitor deployed models for drift, accuracy, and performance, and implement retraining pipelines as needed. 5. Collaboration & Communication . Partner with cross-functional stakeholders to understand business requirements and translate them into analytical solutions. . Present findings, insights, and recommendations to both technical and non-technical audiences through reports, dashboards, and presentations. Qualifications we seek in you! Minimum Qualifications / Skills . Good years of hands-on experience in data science, with a strong focus on forecasting and predictive analytics. . Proficiency in Python and its data science ecosystem (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch, Statsmodels, etc.). . Strong understanding of time series analysis, machine learning algorithms, and NLP techniques. . Experience with data extraction and manipulation using SQL and/or cloud-based data tools. . Familiarity with cloud platforms (AWS, Azure, or GCP) and model deployment workflows. . Ability to work in a fast-paced, agile environment with shifting priorities and tight deadlines. . Excellent problem-solving, analytical thinking, and communication skills. Preferred Qualifications/ Skills . Master&rsquos in computer science, Data Science, Statistics, or a related field Why join Genpact . Lead AI-first transformation - Build and scale AI solutions that redefine industries . Make an impact - Drive change for global enterprises and solve business challenges that matter . Accelerate your career&mdashGain hands-on experience, world-class training, mentorship, and AI certifications to advance your skills . Grow with the best - Learn from top engineers, data scientists, and AI experts in a dynamic, fast-moving workplace . Committed to ethical AI - Work in an environment where governance, transparency, and security are at the core of everything we build . Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Company: Datacrew.ai Location: Chennai (Onsite) Overview Datacrew.ai is seeking a skilled Data Scientist (Demand Forecasting) to join our growing analytics team. In this role, you will design, deploy, and optimize demand prediction models across industries such as food and retail. By leveraging machine learning, time series analysis, and external domain factors , you will deliver actionable insights that drive smarter business decisions. Key Responsibilities Develop and enhance forecasting models using time series, statistical, and ML techniques for SKU- and branch-level demand prediction. Partner with stakeholders to define requirements and identify relevant data sources (historical sales, calendar, promotions, external datasets). Perform feature engineering to integrate seasonality, holidays, promotions, weather, and external drivers into models. Conduct thorough data preprocessing, validation, and analysis to ensure robust and reliable forecasts. Collaborate with data engineering and business teams to deploy models into production and automate recurring forecasts. Track and evaluate model performance using MAE, RMSE, MAPE , and refine models based on results. Prepare documentation, dashboards, and presentations for technical and business audiences. Stay current on advances in time series forecasting, ML, and demand analytics . Required Skills & Experience Bachelor’s/Master’s in Data Science, Statistics, Computer Science, Operations Research , or related field. 4–5 years’ experience in forecasting/analytics (retail, QSR, FMCG, or manufacturing preferred). Hands-on expertise in: Time series models : ARIMA/SARIMA, Exponential Smoothing, Prophet Machine learning models : XGBoost, LightGBM, Random Forest, Neural Networks for time series Proficiency in Python (pandas, scikit-learn, statsmodels, Prophet, etc.); SQL is a plus. Experience in feature engineering with holiday/event calendars and external data. Familiarity with visualization tools (Tableau, Power BI, matplotlib, seaborn). Strong problem-solving, detail orientation, and business translation skills . Excellent communication and collaboration abilities. Preferred Qualifications Experience deploying forecasting models in production/cloud environments . Knowledge of retail/restaurant analytics at SKU and store/branch level. Exposure to big data tools, cloud platforms (AWS, GCP, Azure), and workflow automation. Experience with deep learning models for time series (LSTM, GRU).

Job Title: Quantitative Analyst (Forex) Location: Indore, MP, India (Onsite only - Work from office) Experience Level: 2–5 years Employment Type: Full-time Role Overview Tecnomi is seeking a talented Quantitative Analyst to join our team full-time and play a key role in building, validating, and optimizing systematic forex trading strategies. You will work closely with the project owner and development team to develop actionable models, implement risk frameworks, and contribute to data-driven insights. This full-time position offers the opportunity to drive innovative solutions in a collaborative environment, with a focus on long-term project impact. Key Responsibilities Strategy Development: Design, test, and optimize quantitative trading strategies using price data, volatility measures, sentiment indicators, and macroeconomic variables. Modeling & Backtesting: Build robust forecasting models (e.g., time-series, LSTM/Transformer hybrids) and perform rigorous backtesting to ensure reliability. Risk Frameworks: Develop and integrate risk-control tools (e.g., Value-at-Risk, drawdown limits, exposure thresholds) while aligning with compliance best practices. Data Integration: Aggregate and analyze multi-source data (news feeds, order-book snapshots, economic calendars) for model inputs and enhancements. Mentorship: Provide ongoing guidance and knowledge-sharing sessions to educate non-technical team members, including the project owner, on forex fundamentals and quantitative concepts. Collaboration & Documentation: Work with development teams to integrate model outputs into systems; maintain clear, comprehensive documentation of assumptions, processes, and results. Required Qualifications 3–5 years of experience in quantitative research, preferably in forex or systematic trading. Hands-on experience with backtesting platforms and statistical validation techniques. Strong understanding of FX market dynamics, macro drivers, and risk modeling. Excellent communication and teaching skills to mentor non-experts effectively. Bachelor’s or Master’s degree in Quantitative Finance, Mathematics, Statistics, or a related field. Verifiable 2-year portfolio showcasing prior models, backtests, or strategy reports. Preferred Skills Experience across multiple forex instruments or asset classes. Proficiency in Python or R (e.g., pandas, NumPy, statsmodels, scikit-learn). Familiarity with regulatory frameworks (e.g., RBI/FEMA). Exposure to tools like QuantConnect, MLflow, or similar platforms.

About OnebyZero: OnebyZero is a dynamic and fast-growing AI consulting company based in Singapore. We provide cutting-edge solutions that help businesses transform and thrive in the digital age. Our services blend deep industry expertise, strategy, technology, and data-driven insights to deliver business outcomes. We utilize data, artificial intelligence, and machine learning to unlock new opportunities and drive growth. Our mission is to empower businesses with innovative Data and AI solutions, fostering transformative growth and sustainable success. As a Data Scientist / Machine Learning Engineer, you will play a crucial role in the development and implementation of cutting-edge artificial intelligence products and solutions for our customers. You will be working on a variety of challenging problems involving descriptive, diagnostic, predictive and prescriptive analytics with customers in different industries such as financial services, telecommunications, retail and gaming. You will be tasked with building and operationalizing models such as customer segmentation models, purchase propensity models, recommendation models, churn models, anomaly detection models, time-series prediction models, etc. You may use a variety of algorithms from packages such as scikit-learn, statsmodels, xgboost, tensorflow and pytorch. You’ll also use state-of-the-art MLOps practices to help evaluate different models, manage them and deploy them to production. Finally, we are looking for creative thinkers to help us innovate as we work without customers and help develop reusable assets that can work across different customer engagements. Since you’ll be working on deploying models in production, you are also responsible for upholding a high standard of code quality, and writing and maintaining documentation and tests for the code you write and models you develop. Requirements Basic Qualifications Degree in Computer Science or related field from a top university. Preference will be given to candidates with MS or PhD degrees. 2-4 years experience in Machine Learning or similar roles Skills we are Looking For Proficiency in data mining and machine learning techniques Understanding of basic software engineering design principles, and the ability to write clean, well-structured, maintainable and testable code Experience with Python and its machine learning/data mining toolkits, such as pandas, scipy, numpy, scikit-learn, prophet, xgboost, tensorflow and pytorch on Linux Experience using data science notebooks like Jupyter Good presentation and communication skills, and ability to interact with customers. Preferred Qualifications Experience with SQL and NoSQL databases Experience in working with Big Data systems (such as Databricks, Kafka, Flink, etc.). Experience in distributed ML techniques (such as Ray) Experience in telecommunications, financial services, or retail domains Experience in other programming languages, especially Javascript Knowledge of data visualization packages, in Python and outside Experience in BI tools like Tableau, PowerBI, Apache Superset, etc. Have an AWS (or Azure or GCP) ML Certification Benefits We provide a competitive salary and benefits package, a vibrant work environment, and numerous opportunities for professional growth. You'll have the opportunity to work with a team of industry experts on exciting projects that transform businesses and create significant value. Join us to revolutionize the way companies leverage technology for digital transformation. OnebyZero is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.