Senior Data Analyst - Dow Jones Energy Product Management
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). Do NOT repeat the job title as a heading. We should include sections only when posting has real specific content.
We have content: About The Team (description). Could be a section heading "About the Team"? Not listed but we can use similar. The instruction gave examples but not exclusive; we can use headings like About the Team, About the Role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to decide which sections have content.
Posting includes:
- About The Team (description)
- About The Role (description)
- You Will (list of responsibilities)
- You Have (requirements/qualifications)
- Our Benefits (list)
- Base Pay Range: $75,000 - $95,000 (Pay)
- No explicit schedule.
Thus we can have sections: About the Team, About the Role, Responsibilities (You Will), Requirements/Qualifications (You Have), Benefits, Pay.
We should not include schedule.
We need to use for each section heading. Use - for any list of duties/requirements/benefits. Use
for prose.
We must preserve all substantive information, not invent or summarize away detail. Remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, application instructions. So we need to strip out the EEO statement, accommodation, privacy notice, etc. Also remove "Learn More About Us And Our Benefits Click Here." maybe considered boilerplate? It's a call to action; maybe remove as it's not substantive. Also remove "Business Area: Dow Jones - Energy Job Category: Data Analytics/Warehousing & Business Intelligence Union Status Non-Union role". Might be metadata; we can fold minor metadata into a short
or drop it. The instruction: do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short
or drop it. So we could include a short paragraph with Business Area, Job Category, Union Status, Base Pay Range? But Pay we already have separate section. We could include a short paragraph for Business Area, Job Category, Union Status. Or drop them. Safer to include a short
after About the Team maybe.
We need to preserve all substantive information: The description of team, role, responsibilities, qualifications, benefits, pay range.
Let's extract.
About The Team:
"Dow Jones Energy delivers trusted price transparency, benchmarks, analytics, news, and insights across the global energy, chemicals, metals, and fuel supply value chains. Our offerings support institutional investors, analysts, and traders navigating spot, wholesale, and retail markets, as well as emerging segments tied to the global energy transition. Through authoritative data, real-time intelligence, and deep market expertise, Dow Jones Energy enables financial professionals to mitigate risk and make high-stakes commercial decisions in volatile, fast-evolving global markets."
About The Role:
"This is an exciting time to join our small but growing Commercial Product Management team where you will be supporting a number of key sectors including: Energy & Feedstocks, Coal, Metals and Mining, Renewables & Clean Energy and Chemicals. We are seeking a highly analytical and detail-oriented Senior Data Analyst to support business performance, revenue management, customer analytics, sales operations, product strategy, and executive decision-making. The position requires a combination of advanced Excel, SQL, Python, business intelligence, financial analysis, data visualization, and strong business judgment. You will work across large and complex datasets to develop reporting, dashboards, analytical models, and actionable insights for product and leadership teams. You are comfortable working independently on ambiguous analytical problems, reconciling data from multiple sources, automating recurring processes, and communicating findings to both technical and non-technical stakeholders. You will also serve as a key analytical partner to the Product, Sales, Finance, Customer Care, Consulting, and leadership teams. You will report to the Vice President - Product Management."
You Will (Responsibilities) list:
- Commercial & Revenue Optimization: Own end-to-end reporting for the Book of Business (ACV, renewals, new business, win/loss), building bottoms-up financial models, scenario analyses, and churn diagnostics to drive pricing, budgeting, and revenue retention strategies
- Advanced Data Engineering & SQL: Query, transform, and aggregate complex datasets across multiple source systems using optimized SQL to resolve data discrepancies and ensure unified, cross-system reporting integrity
- Data Quality & Governance: Establish rigorous validation processes, data cleansing protocols, and repeatable quality assurance checks to maintain accuracy and reliability across all core business metrics
- Business Intelligence & Dashboards: Design and maintain scalable, user-friendly Power BI/Looker Studio dashboards that deliver actionable visibility into product performance, sales activity, customer health, and financial KPIs for non-technical stakeholders
- Process Automation & AI Integration: Streamline recurring workflows using SQL, Python, Excel/VBA, and Power Query, while exploring AI/BigQuery solutions to scale self-service analytics and reduce manual reporting dependencies
- Customer & Usage Behavioral Analytics: Synthesize product adoption, API/web activity, and usage data into customer health scores and engagement metrics that empower Sales and Account Management teams to mitigate churn Risk
- Product Portfolio Strategy: Conduct product performance and entitlement analyses to evaluate pricing packages, support new product launches, and inform portfolio optimization or sunsetting initiatives
- Cross-Functional Stakeholder Partnership: Serve as a strategic analytics partner across Sales, Finance, Product, and executive leadership, effectively communicating complex methodologies and managing ad-hoc analytical priorities to guide business decisions
You Have (Requirements/Qualifications):
- 3+ years’ professional experience in data analytics, commercial analytics, financial analysis, market research, or a related analytical role
- Advanced proficiency in Microsoft Excel; including complex formulas, PivotTables, XLOOKUP, INDEX/MATCH, SUMIFS, nested logic, and data manipulation, VBA, Excel Macros, or Power Query
- Experience with some or all of the following technologies: Python (particularly Pandas and data analysis/automation) BigQuery, Snowflake, SQL Server, Athena, or other cloud/data warehouse platforms Power BI, Looker Studio, Tableau, or similar BI platforms
- Experience with B2B data/information, industry analysis, and/or applied software products (highly desirable)
- Domain knowledge in chemicals/energy or other related industry areas
- An interest to pursue a career in product management and want to leverage your existing analytical skill set while deepening your product management capabilities and expertise
- Bachelor's degree in Data Analytics, Mathematics, Statistics, Economics, Finance, Business, Computer Science, or a related quantitative field -OR- equivalent work experience
Benefits list:
- Comprehensive Healthcare Plans
- Paid Time Off
- Retirement Plans
- Comprehensive Insurance Plans
- Lifestyle Programs & Wellness Resources
- Education Benefits
- Family Care Benefits & Caregiving Support
- Commuter Transit Program
- Subscription Discounts
- Employee Referral Program
- Financial Health Programs
- Cybersecurity Protection
Pay: Base Pay Range: $75,000 - $95,000
We also have statement: "We’re committed to offering competitive and flexible compensation to attract top talent. This pay range reflects our good faith estimate for the role and may vary based on a candidate’s experience, skills, location, and other relevant factors. For bonus-eligible roles, targets are determined based on multiple considerations, including market benchmarks and individual contributions. For benefits-eligible roles, we offer a comprehensive and competitive benefits package covering health, retirement, wellbeing, and more, along with optional benefits to meet the diverse needs of our employees." This is substantive about pay and benefits; we could incorporate into Pay and Benefits sections as prose.
We should not include boilerplate like "Equal Opportunity Employer..." etc.
We also have "Dow Jones is a global provider..." etc. That's boilerplate about company; maybe we can drop as not substantive to role. The instruction: Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The company description might be considered boilerplate but could be part of About The Team? Already we have team description. The later paragraphs about Dow Jones history etc are likely boilerplate; we can drop.
Thus final HTML:
About the Team
Dow Jones Energy delivers trusted price transparency, benchmarks, analytics, news, and insights across the global energy, chemicals, metals, and fuel supply value chains. Our offerings support institutional investors, analysts, and traders navigating spot, wholesale, and retail markets, as well as emerging segments tied to the global energy transition. Through authoritative data, real-time intelligence, and deep market expertise, Dow Jones Energy enables financial professionals to mitigate risk and make high-stakes commercial decisions in volatile, fast-evolving global markets.
About the Role
This is an exciting time to join our small but growing Commercial Product Management team where you will be supporting a number of key sectors including: Energy & Feedstocks, Coal, Metals and Mining, Renewables & Clean Energy and Chemicals. We are seeking a highly analytical and detail-oriented Senior Data Analyst to support business performance, revenue management, customer analytics, sales operations, product strategy, and executive decision-making. The position requires a combination of advanced Excel, SQL, Python, business intelligence, financial analysis, data visualization, and strong business judgment. You will work across large and complex datasets to develop reporting, dashboards, analytical models, and actionable insights for product and leadership teams. You are comfortable working independently on ambiguous analytical problems, reconciling data from multiple sources, automating recurring processes, and communicating findings to both technical and non-technical stakeholders. You will also serve as a key analytical partner to the Product, Sales, Finance, Customer Care, Consulting, and leadership teams. You will report to the Vice President - Product Management.
Responsibilities
- Commercial & Revenue Optimization: Own end-to-end reporting for the Book of Business (ACV, renewals, new business, win/loss), building bottoms-up financial models, scenario analyses, and churn diagnostics to drive pricing, budgeting, and revenue retention strategies
- Advanced Data Engineering & SQL: Query, transform, and aggregate complex datasets across multiple source systems using optimized SQL to resolve data discrepancies and ensure unified, cross-system reporting integrity
- Data Quality & Governance: Establish rigorous validation processes, data cleansing protocols, and repeatable quality assurance checks to maintain accuracy and reliability across all core business metrics
- Business Intelligence & Dashboards: Design and maintain scalable, user-friendly Power BI/Looker Studio dashboards that deliver actionable visibility into product performance, sales activity, customer health, and financial KPIs for non-technical stakeholders
- Process Automation & AI Integration: Streamline recurring workflows using SQL, Python, Excel/VBA, and Power Query, while exploring AI/BigQuery solutions to scale self-service analytics and reduce manual reporting dependencies
- Customer & Usage Behavioral Analytics: Synthesize product adoption, API/web activity, and usage data into customer health scores and engagement metrics that empower Sales and Account Management teams to mitigate churn Risk
- Product Portfolio Strategy: Conduct product performance and entitlement analyses to evaluate pricing packages, support new product launches, and inform portfolio optimization or sunsetting initiatives
- Cross-Functional Stakeholder Partnership: Serve as a strategic analytics partner across Sales, Finance, Product, and executive leadership, effectively communicating complex methodologies and managing ad-hoc analytical priorities to guide business decisions
Requirements
- 3+ years’ professional experience in data analytics, commercial analytics, financial analysis, market research, or a related analytical role
- Advanced proficiency in Microsoft Excel; including complex formulas, PivotTables, XLOOKUP, INDEX/MATCH, SUMIFS, nested logic, and data manipulation, VBA, Excel Macros, or Power Query
- Experience
- for any list of duties/requirements/benefits. Use
for prose. We must preserve all substantive information, not invent or summarize away detail. Remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, application instructions. So we need to strip out the EEO statement, accommodation, privacy notice, etc. Also remove "Learn More About Us And Our Benefits Click Here." maybe considered boilerplate? It's a call to action; maybe remove as it's not substantive. Also remove "Business Area: Dow Jones - Energy Job Category: Data Analytics/Warehousing & Business Intelligence Union Status Non-Union role". Might be metadata; we can fold minor metadata into a short
or drop it. The instruction: do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short
or drop it. So we could include a short paragraph with Business Area, Job Category, Union Status, Base Pay Range? But Pay we already have separate section. We could include a short paragraph for Business Area, Job Category, Union Status. Or drop them. Safer to include a short
after About the Team maybe. We need to preserve all substantive information: The description of team, role, responsibilities, qualifications, benefits, pay range. Let's extract. About The Team: "Dow Jones Energy delivers trusted price transparency, benchmarks, analytics, news, and insights across the global energy, chemicals, metals, and fuel supply value chains. Our offerings support institutional investors, analysts, and traders navigating spot, wholesale, and retail markets, as well as emerging segments tied to the global energy transition. Through authoritative data, real-time intelligence, and deep market expertise, Dow Jones Energy enables financial professionals to mitigate risk and make high-stakes commercial decisions in volatile, fast-evolving global markets." About The Role: "This is an exciting time to join our small but growing Commercial Product Management team where you will be supporting a number of key sectors including: Energy & Feedstocks, Coal, Metals and Mining, Renewables & Clean Energy and Chemicals. We are seeking a highly analytical and detail-oriented Senior Data Analyst to support business performance, revenue management, customer analytics, sales operations, product strategy, and executive decision-making. The position requires a combination of advanced Excel, SQL, Python, business intelligence, financial analysis, data visualization, and strong business judgment. You will work across large and complex datasets to develop reporting, dashboards, analytical models, and actionable insights for product and leadership teams. You are comfortable working independently on ambiguous analytical problems, reconciling data from multiple sources, automating recurring processes, and communicating findings to both technical and non-technical stakeholders. You will also serve as a key analytical partner to the Product, Sales, Finance, Customer Care, Consulting, and leadership teams. You will report to the Vice President - Product Management." You Will (Responsibilities) list: - Commercial & Revenue Optimization: Own end-to-end reporting for the Book of Business (ACV, renewals, new business, win/loss), building bottoms-up financial models, scenario analyses, and churn diagnostics to drive pricing, budgeting, and revenue retention strategies - Advanced Data Engineering & SQL: Query, transform, and aggregate complex datasets across multiple source systems using optimized SQL to resolve data discrepancies and ensure unified, cross-system reporting integrity - Data Quality & Governance: Establish rigorous validation processes, data cleansing protocols, and repeatable quality assurance checks to maintain accuracy and reliability across all core business metrics - Business Intelligence & Dashboards: Design and maintain scalable, user-friendly Power BI/Looker Studio dashboards that deliver actionable visibility into product performance, sales activity, customer health, and financial KPIs for non-technical stakeholders - Process Automation & AI Integration: Streamline recurring workflows using SQL, Python, Excel/VBA, and Power Query, while exploring AI/BigQuery solutions to scale self-service analytics and reduce manual reporting dependencies - Customer & Usage Behavioral Analytics: Synthesize product adoption, API/web activity, and usage data into customer health scores and engagement metrics that empower Sales and Account Management teams to mitigate churn Risk - Product Portfolio Strategy: Conduct product performance and entitlement analyses to evaluate pricing packages, support new product launches, and inform portfolio optimization or sunsetting initiatives - Cross-Functional Stakeholder Partnership: Serve as a strategic analytics partner across Sales, Finance, Product, and executive leadership, effectively communicating complex methodologies and managing ad-hoc analytical priorities to guide business decisions You Have (Requirements/Qualifications): - 3+ years’ professional experience in data analytics, commercial analytics, financial analysis, market research, or a related analytical role - Advanced proficiency in Microsoft Excel; including complex formulas, PivotTables, XLOOKUP, INDEX/MATCH, SUMIFS, nested logic, and data manipulation, VBA, Excel Macros, or Power Query - Experience with some or all of the following technologies: Python (particularly Pandas and data analysis/automation) BigQuery, Snowflake, SQL Server, Athena, or other cloud/data warehouse platforms Power BI, Looker Studio, Tableau, or similar BI platforms - Experience with B2B data/information, industry analysis, and/or applied software products (highly desirable) - Domain knowledge in chemicals/energy or other related industry areas - An interest to pursue a career in product management and want to leverage your existing analytical skill set while deepening your product management capabilities and expertise - Bachelor's degree in Data Analytics, Mathematics, Statistics, Economics, Finance, Business, Computer Science, or a related quantitative field -OR- equivalent work experience Benefits list: - Comprehensive Healthcare Plans - Paid Time Off - Retirement Plans - Comprehensive Insurance Plans - Lifestyle Programs & Wellness Resources - Education Benefits - Family Care Benefits & Caregiving Support - Commuter Transit Program - Subscription Discounts - Employee Referral Program - Financial Health Programs - Cybersecurity Protection Pay: Base Pay Range: $75,000 - $95,000 We also have statement: "We’re committed to offering competitive and flexible compensation to attract top talent. This pay range reflects our good faith estimate for the role and may vary based on a candidate’s experience, skills, location, and other relevant factors. For bonus-eligible roles, targets are determined based on multiple considerations, including market benchmarks and individual contributions. For benefits-eligible roles, we offer a comprehensive and competitive benefits package covering health, retirement, wellbeing, and more, along with optional benefits to meet the diverse needs of our employees." This is substantive about pay and benefits; we could incorporate into Pay and Benefits sections as prose. We should not include boilerplate like "Equal Opportunity Employer..." etc. We also have "Dow Jones is a global provider..." etc. That's boilerplate about company; maybe we can drop as not substantive to role. The instruction: Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The company description might be considered boilerplate but could be part of About The Team? Already we have team description. The later paragraphs about Dow Jones history etc are likely boilerplate; we can drop. Thus final HTML:
About the Team
Dow Jones Energy delivers trusted price transparency, benchmarks, analytics, news, and insights across the global energy, chemicals, metals, and fuel supply value chains. Our offerings support institutional investors, analysts, and traders navigating spot, wholesale, and retail markets, as well as emerging segments tied to the global energy transition. Through authoritative data, real-time intelligence, and deep market expertise, Dow Jones Energy enables financial professionals to mitigate risk and make high-stakes commercial decisions in volatile, fast-evolving global markets.
About the Role
This is an exciting time to join our small but growing Commercial Product Management team where you will be supporting a number of key sectors including: Energy & Feedstocks, Coal, Metals and Mining, Renewables & Clean Energy and Chemicals. We are seeking a highly analytical and detail-oriented Senior Data Analyst to support business performance, revenue management, customer analytics, sales operations, product strategy, and executive decision-making. The position requires a combination of advanced Excel, SQL, Python, business intelligence, financial analysis, data visualization, and strong business judgment. You will work across large and complex datasets to develop reporting, dashboards, analytical models, and actionable insights for product and leadership teams. You are comfortable working independently on ambiguous analytical problems, reconciling data from multiple sources, automating recurring processes, and communicating findings to both technical and non-technical stakeholders. You will also serve as a key analytical partner to the Product, Sales, Finance, Customer Care, Consulting, and leadership teams. You will report to the Vice President - Product Management.
Responsibilities
- Commercial & Revenue Optimization: Own end-to-end reporting for the Book of Business (ACV, renewals, new business, win/loss), building bottoms-up financial models, scenario analyses, and churn diagnostics to drive pricing, budgeting, and revenue retention strategies
- Advanced Data Engineering & SQL: Query, transform, and aggregate complex datasets across multiple source systems using optimized SQL to resolve data discrepancies and ensure unified, cross-system reporting integrity
- Data Quality & Governance: Establish rigorous validation processes, data cleansing protocols, and repeatable quality assurance checks to maintain accuracy and reliability across all core business metrics
- Business Intelligence & Dashboards: Design and maintain scalable, user-friendly Power BI/Looker Studio dashboards that deliver actionable visibility into product performance, sales activity, customer health, and financial KPIs for non-technical stakeholders
- Process Automation & AI Integration: Streamline recurring workflows using SQL, Python, Excel/VBA, and Power Query, while exploring AI/BigQuery solutions to scale self-service analytics and reduce manual reporting dependencies
- Customer & Usage Behavioral Analytics: Synthesize product adoption, API/web activity, and usage data into customer health scores and engagement metrics that empower Sales and Account Management teams to mitigate churn Risk
- Product Portfolio Strategy: Conduct product performance and entitlement analyses to evaluate pricing packages, support new product launches, and inform portfolio optimization or sunsetting initiatives
- Cross-Functional Stakeholder Partnership: Serve as a strategic analytics partner across Sales, Finance, Product, and executive leadership, effectively communicating complex methodologies and managing ad-hoc analytical priorities to guide business decisions
Requirements
- 3+ years’ professional experience in data analytics, commercial analytics, financial analysis, market research, or a related analytical role
- Advanced proficiency in Microsoft Excel; including complex formulas, PivotTables, XLOOKUP, INDEX/MATCH, SUMIFS, nested logic, and data manipulation, VBA, Excel Macros, or Power Query
- Experience