Forecasting Data Scientist
About the role
with paragraph. Responsibilities: list under "Key Responsibilities". Provide bullet list. Qualifications: includes Basic Qualifications and Preferred Qualifications. Could combine underQualifications
with paragraphs/lists. Skills: maybe not separate; but we have many skill mentions in Preferred Qualifications. Could embed in Qualifications. The instruction: prefer few substantive sections over many thin ones. So we could have sections: About the role, Responsibilities, Qualifications, Benefits, Pay, Schedule? Schedule: they mention "Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager." That's schedule info (hybrid). Also "Work Hours Varies upon the needs of the department." That's schedule. So we can include Schedule section. Benefits: they mention comprehensive benefits package includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, Wellness Program. So Benefits section. Pay: salary range $137,400 to $212,500 plus bonus and equity. So Pay section. We should not include sections with placeholder like "commensurate with experience". We have actual numbers. We need to remove boilerplate: EEO, legal, etc. Also remove "Information for US Applicants" maybe keep as part of Pay? Actually salary range is under that heading. We'll keep Pay. We need to format using for section headings, - for lists,
for prose.
We must not repeat job title as heading. Not include Job ID.
We must preserve all substantive information; do not invent or summarize away detail.
Let's extract details:
About Us paragraph: "Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters – to you, to your community, and to the world. Progress starts with you."
Role Summary: "The Data Scientist is responsible for solving complex business problems using advanced data science techniques, AI/ML models, and data-driven frameworks. This role develops and executes a vision for data science capabilities, leading the design and development of large-scale systems and fostering innovation within the team. The Data Scientist collaborates closely with cross-functional teams to integrate data science solutions, communicates technical concepts to stakeholders, and influences business decisions with actionable insights. All roles require digital fluency, including the ability to work with emerging technologies such as Generative AI tools (e.g. ChatGPT, Microsoft Copilot) to support everyday work."
We could combine About Us and Role Summary under About the role? Might be redundant. But we could have About the role include both company description and role summary. That's okay.
Responsibilities list:
- Solve complex business problems using advanced data science techniques, AI/ML models, and frameworks.
- Develop and execute a vision for data science capabilities aligned with business goals.
- Lead the design and development of large-scale data science systems and foster innovation within the team.
- Apply advanced data science techniques and models to drive business impact and stay up-to-date with industry trends.
- Collaborate with cross-functional teams to integrate data science capabilities and communicate complex technical concepts to stakeholders.
- Develop and maintain expertise in multiple programming languages and data science tools.
- Identify opportunities for data science to drive business impact and present results to senior leadership and business partners.
Qualifications:
Basic Qualifications: "2 or more years of work experience with a bachelor’s degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)."
Preferred Qualifications list many items:
- 3 or more years of work experience with a bachelor’s degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD).
- Experience with time series forecasting methodologies, including classical approaches such as SARIMA/SARIMAX or Vector-Autoregression / Vector-Error-Correction, and advanced local/global forecasting methods such as N-HiTS, TFT, DeepAR, NeuralProphet, or similar techniques.
- Familiarity with emerging time series foundation models and generative forecasting approaches, such as TimesFM, TimeGPT, or related AI-driven forecasting tools, with a demonstrated ability to stay current with new developments in forecasting and applied machine learning.
- Experience incorporating AI and automation capabilities into regular data science workflows to improve forecasting accuracy, experimentation speed, model monitoring, optimization, scalability, and overall team efficiency.
- Experience in developing advanced data science models.
- Experience in multiple programming languages (e.g., Python, R, Spark).
- Experience with data science tools and technologies (e.g., TensorFlow, PyTorch, scikit-learn).
- Experience working with real-world data sets and building scalable models from large-scale data.
- Experience working with cross-functional teams (e.g., product, engineering, marketing).
- Experience in project management and meeting deadlines in a fast-moving environment.
- Experience working in global organizations and collaborating with stakeholders and development teams across regions.
- Experience in deep learning, machine learning, recommendation systems, generative models, and statistical analyses.
- Experience working with global organizations and roles requiring collaboration with stakeholders and partners worldwide.
- Previous exposure to financial services or payments industry.
We could combine Basic and Preferred into one list? Might be long. But we can separate Basic Qualifications as a paragraph, then Preferred as a list.
Benefits: "Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program."
Pay: "For roles located in the US, the estimated salary range for this position is $137,400.00 to $ 212,500.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity."
Schedule: "Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager." Also "Work Hours Varies upon the needs of the department." Also maybe travel 5-10% but that's not schedule. Travel is separate but not requested heading. Could include under Schedule? Not needed. We'll include schedule bullet points.
We should not include Travel Requirements as separate section unless we have a heading for Travel; not requested. So we can omit.
We must not include boilerplate like EEO, etc.
Now produce HTML:
About the role
Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters – to you, to your community, and to the world. Progress starts with you.
The Data Scientist is responsible for solving complex business problems using advanced data science techniques, AI/ML models, and data-driven frameworks. This role develops and executes a vision for data science capabilities, leading the design and development of large-scale systems and fostering innovation within the team. The Data Scientist collaborates closely with cross-functional teams to integrate data science solutions, communicates technical concepts to stakeholders, and influences business decisions with actionable insights. All roles require digital fluency, including the ability to work with emerging technologies such as Generative AI tools (e.g. ChatGPT, Microsoft Copilot) to support everyday work.
Responsibilities
- Solve complex business problems using advanced data science techniques, AI/ML models, and frameworks.
- Develop and execute a vision for data science capabilities aligned with business goals.
- Lead the design and development of large-scale data science systems and foster innovation within the team.
- Apply advanced data science techniques and models to drive business impact and stay up-to-date with industry trends.
- Collaborate with cross-functional teams to integrate data science capabilities and communicate complex technical concepts to stakeholders.
- Develop and maintain expertise in multiple programming languages and data science tools.
- Identify opportunities for data science to drive business impact and present results to senior leadership and business partners.
Qualifications
Basic Qualifications: 2 or more years of work experience with a bachelor’s degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD).
Preferred Qualifications:
- 3 or more years of work experience with a bachelor’s degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD).
- Experience with time series forecasting methodologies, including classical approaches such as SARIMA/SARIMAX or Vector-Autoregression / Vector-Error-Correction, and advanced local/global forecasting methods such as N-HiTS, TFT, DeepAR, NeuralProphet, or similar techniques.
- Familiarity with emerging time series foundation models and generative forecasting approaches, such as TimesFM, TimeGPT, or related AI-driven forecasting tools, with a demonstrated ability to stay current with new developments in forecasting and applied machine learning.
- Experience incorporating AI and automation capabilities into regular data science workflows to improve forecasting accuracy, experimentation speed, model monitoring, optimization, scalability, and overall team efficiency.
- Experience in developing advanced data science models.
- Experience in multiple programming languages (e.g., Python, R, Spark).
- Experience with data science tools and technologies (e.g., TensorFlow, PyTorch, scikit-learn).
- Experience working with real-world data sets and building scalable models from large-scale data.
- Experience working with cross-functional teams (e.g., product, engineering, marketing).
- Experience in project management and meeting deadlines in a fast-moving environment.
- Experience working in global organizations and collaborating with stakeholders and development teams across regions.
- Experience in deep learning, machine learning, recommendation systems, generative models, and statistical analyses.
- Experience working with global organizations and roles requiring collaboration with stakeholders and partners worldwide.
- Previous exposure to financial services or payments industry.
Benefits
Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.
Pay
For roles located in the US, the estimated salary range for this position is $137,400.00 to $212,500.00 USD per year, which may include potential sales incentive
for prose. We must not repeat job title as heading. Not include Job ID. We must preserve all substantive information; do not invent or summarize away detail. Let's extract details: About Us paragraph: "Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters – to you, to your community, and to the world. Progress starts with you." Role Summary: "The Data Scientist is responsible for solving complex business problems using advanced data science techniques, AI/ML models, and data-driven frameworks. This role develops and executes a vision for data science capabilities, leading the design and development of large-scale systems and fostering innovation within the team. The Data Scientist collaborates closely with cross-functional teams to integrate data science solutions, communicates technical concepts to stakeholders, and influences business decisions with actionable insights. All roles require digital fluency, including the ability to work with emerging technologies such as Generative AI tools (e.g. ChatGPT, Microsoft Copilot) to support everyday work." We could combine About Us and Role Summary under About the role? Might be redundant. But we could have About the role include both company description and role summary. That's okay. Responsibilities list: - Solve complex business problems using advanced data science techniques, AI/ML models, and frameworks. - Develop and execute a vision for data science capabilities aligned with business goals. - Lead the design and development of large-scale data science systems and foster innovation within the team. - Apply advanced data science techniques and models to drive business impact and stay up-to-date with industry trends. - Collaborate with cross-functional teams to integrate data science capabilities and communicate complex technical concepts to stakeholders. - Develop and maintain expertise in multiple programming languages and data science tools. - Identify opportunities for data science to drive business impact and present results to senior leadership and business partners. Qualifications: Basic Qualifications: "2 or more years of work experience with a bachelor’s degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)." Preferred Qualifications list many items: - 3 or more years of work experience with a bachelor’s degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD). - Experience with time series forecasting methodologies, including classical approaches such as SARIMA/SARIMAX or Vector-Autoregression / Vector-Error-Correction, and advanced local/global forecasting methods such as N-HiTS, TFT, DeepAR, NeuralProphet, or similar techniques. - Familiarity with emerging time series foundation models and generative forecasting approaches, such as TimesFM, TimeGPT, or related AI-driven forecasting tools, with a demonstrated ability to stay current with new developments in forecasting and applied machine learning. - Experience incorporating AI and automation capabilities into regular data science workflows to improve forecasting accuracy, experimentation speed, model monitoring, optimization, scalability, and overall team efficiency. - Experience in developing advanced data science models. - Experience in multiple programming languages (e.g., Python, R, Spark). - Experience with data science tools and technologies (e.g., TensorFlow, PyTorch, scikit-learn). - Experience working with real-world data sets and building scalable models from large-scale data. - Experience working with cross-functional teams (e.g., product, engineering, marketing). - Experience in project management and meeting deadlines in a fast-moving environment. - Experience working in global organizations and collaborating with stakeholders and development teams across regions. - Experience in deep learning, machine learning, recommendation systems, generative models, and statistical analyses. - Experience working with global organizations and roles requiring collaboration with stakeholders and partners worldwide. - Previous exposure to financial services or payments industry. We could combine Basic and Preferred into one list? Might be long. But we can separate Basic Qualifications as a paragraph, then Preferred as a list. Benefits: "Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program." Pay: "For roles located in the US, the estimated salary range for this position is $137,400.00 to $ 212,500.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity." Schedule: "Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager." Also "Work Hours Varies upon the needs of the department." Also maybe travel 5-10% but that's not schedule. Travel is separate but not requested heading. Could include under Schedule? Not needed. We'll include schedule bullet points. We should not include Travel Requirements as separate section unless we have a heading for Travel; not requested. So we can omit. We must not include boilerplate like EEO, etc. Now produce HTML:
About the role
Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters – to you, to your community, and to the world. Progress starts with you.
The Data Scientist is responsible for solving complex business problems using advanced data science techniques, AI/ML models, and data-driven frameworks. This role develops and executes a vision for data science capabilities, leading the design and development of large-scale systems and fostering innovation within the team. The Data Scientist collaborates closely with cross-functional teams to integrate data science solutions, communicates technical concepts to stakeholders, and influences business decisions with actionable insights. All roles require digital fluency, including the ability to work with emerging technologies such as Generative AI tools (e.g. ChatGPT, Microsoft Copilot) to support everyday work.
Responsibilities
- Solve complex business problems using advanced data science techniques, AI/ML models, and frameworks.
- Develop and execute a vision for data science capabilities aligned with business goals.
- Lead the design and development of large-scale data science systems and foster innovation within the team.
- Apply advanced data science techniques and models to drive business impact and stay up-to-date with industry trends.
- Collaborate with cross-functional teams to integrate data science capabilities and communicate complex technical concepts to stakeholders.
- Develop and maintain expertise in multiple programming languages and data science tools.
- Identify opportunities for data science to drive business impact and present results to senior leadership and business partners.
Qualifications
Basic Qualifications: 2 or more years of work experience with a bachelor’s degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD).
Preferred Qualifications:
- 3 or more years of work experience with a bachelor’s degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD).
- Experience with time series forecasting methodologies, including classical approaches such as SARIMA/SARIMAX or Vector-Autoregression / Vector-Error-Correction, and advanced local/global forecasting methods such as N-HiTS, TFT, DeepAR, NeuralProphet, or similar techniques.
- Familiarity with emerging time series foundation models and generative forecasting approaches, such as TimesFM, TimeGPT, or related AI-driven forecasting tools, with a demonstrated ability to stay current with new developments in forecasting and applied machine learning.
- Experience incorporating AI and automation capabilities into regular data science workflows to improve forecasting accuracy, experimentation speed, model monitoring, optimization, scalability, and overall team efficiency.
- Experience in developing advanced data science models.
- Experience in multiple programming languages (e.g., Python, R, Spark).
- Experience with data science tools and technologies (e.g., TensorFlow, PyTorch, scikit-learn).
- Experience working with real-world data sets and building scalable models from large-scale data.
- Experience working with cross-functional teams (e.g., product, engineering, marketing).
- Experience in project management and meeting deadlines in a fast-moving environment.
- Experience working in global organizations and collaborating with stakeholders and development teams across regions.
- Experience in deep learning, machine learning, recommendation systems, generative models, and statistical analyses.
- Experience working with global organizations and roles requiring collaboration with stakeholders and partners worldwide.
- Previous exposure to financial services or payments industry.
Benefits
Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.
Pay
For roles located in the US, the estimated salary range for this position is $137,400.00 to $212,500.00 USD per year, which may include potential sales incentive