Jobs › Companies › Synechron › Risk & Reporting Analyst – Alternative Investments, Portfolio Analytics & Excel/SQL

About this Risk & Reporting Analyst – Alternative Investments, Portfolio Analytics & Excel/SQL role at Synechron

Synechron · Onsite · Hyderabad Eco Park

Job Summary

Synechron is seeking a Risk & Reporting Analyst with experience in asset management, investment banking, fund administration, or financial services. The role will support private credit, private equity, investment reporting, portfolio analytics, and recurring investor-reporting workflows.

The position will analyze portfolio data, calculate alternative-investment performance metrics, prepare reporting outputs, validate data quality, and translate complex information into clear analysis for internal and external stakeholders.

The role will contribute to business objectives by improving reporting accuracy, strengthening data controls, supporting informed investment decisions, and delivering timely, consistent, and transparent portfolio and investor insights.


Software Requirements

Required Software Skills

  • Microsoft Excel: Strong hands-on experience with formulas, pivot tables, lookups, Power Query, data validation, reconciliation, and reporting automation.
  • SQL: Working experience querying, validating, joining, and analyzing structured financial and portfolio data.
  • Power BI: Experience creating or supporting dashboards, visualizations, data models, and reporting outputs is required where applicable.
  • Data validation tools: Ability to apply completeness, accuracy, consistency, reconciliation, exception, and reasonableness checks.
  • Investment reporting tools: Experience supporting recurring investor-reporting workflows, portfolio analytics, exposure reporting, performance reporting, and attribution outputs.
  • Reporting documentation: Ability to maintain reporting specifications, data dictionaries, calculation logic, control documentation, and process procedures.

Preferred Software Skills

  • Python: Experience with data analysis, reporting automation, data validation, and repeatable analytical workflows.
  • Approved GenAI tools: Experience with prompt engineering for analysis, documentation, workflow support, or reporting activities, subject to applicable controls.
  • Azure or Microsoft Fabric: Familiarity with cloud-based data, analytics, semantic models, and reporting environments.
  • Deployment pipelines: Exposure to deployment and release processes for reporting, data, or analytical solutions.
  • Jira and Confluence: Working knowledge of work-item management, process documentation, requirements tracking, and knowledge sharing.
  • Investor-platform workflows: Familiarity with eFront-style workflows or comparable investment and portfolio reporting platforms.

Version and Experience Guidance

  • Specific software versions are not mandated in the requirements.
  • Candidates should have experience with current, production-supported versions of Excel, SQL, Power BI, Python, and relevant reporting or analytics tools.
  • Candidates should be able to assess data and reporting-tool compatibility, document changes, validate outputs, and follow controlled release practices.
  • Experience should include practical delivery of recurring reports, portfolio analysis, financial data validation, or related reporting outputs.


Overall Responsibilities

  • Prepare, review, validate, and maintain recurring investment and investor-reporting outputs.
  • Analyze portfolio exposure attributes, performance information, attribution data, benchmarks, and related investment metrics.
  • Apply and explain alternative-investment performance measures, including:Time-Weighted Return (TWR)Money-Weighted Return (MWR)Internal Rate of Return (IRR)Multiple on Invested Capital (MOIC)Total Value to Paid-In (TVPI)Distributions to Paid-In (DPI)Residual Value to Paid-In (RVPI)
  • Support portfolio analytics across private credit, private equity, and other alternative-investment strategies.
  • Review and reconcile source data, calculated metrics, reporting outputs, and investor-facing information.
  • Use Excel, SQL, Power BI, and related tools to analyze data and produce clear reporting.
  • Investigate data exceptions, calculation differences, missing information, and reporting breaks.
  • Maintain recurring reporting workflows, calculation logic, control procedures, and supporting documentation.
  • Collaborate with investment, operations, finance, fund administration, technology, risk, and reporting teams.
  • Own assigned workstreams from requirements clarification through analysis, validation, review, and delivery.
  • Support the development of dashboards, semantic models, reporting templates, and repeatable analytical processes.
  • Apply appropriate data controls when using approved GenAI tools for analysis, documentation, or workflow support.
  • Contribute to process improvement, reporting automation, data-quality enhancement, and sustainable resource use.
  • Ensure reporting activities support accuracy, timeliness, transparency, confidentiality, and applicable governance standards.
  • Track deliverables, dependencies, risks, issues, and stakeholder feedback to support predictable reporting outcomes.


Technical Skills (By Category)


Programming Languages

Essential

  • SQL for data extraction, transformation, reconciliation, validation, and analysis.
  • Ability to interpret calculation logic and translate investment metrics into repeatable analytical processes.
  • Ability to work with formulas, structured data, validation rules, and reporting calculations in Excel.
  • Ability to document analytical logic and reproduce reporting results.

Preferred

  • Python for data analysis, reporting automation, validation, and workflow improvement.
  • Experience developing reusable scripts or utilities for data preparation and report generation.
  • Familiarity with programming concepts that support analytical model testing and deployment.

Databases/Data Management

Essential

  • Experience working with structured and unstructured financial, portfolio, investment, or investor-reporting data.
  • Understanding of portfolio exposure attributes, investment records, performance data, benchmarks, attribution data, and reporting hierarchies.
  • Ability to perform data reconciliation, validation, completeness checks, exception analysis, and reasonableness testing.
  • Understanding of data lineage, definitions, source-to-report mapping, data ownership, and reporting controls.
  • Ability to maintain data quality and integrity across recurring reporting processes.

Preferred

  • Experience with semantic models, data marts, data warehouses, or analytical data platforms.
  • Familiarity with alternative-investment accounting concepts and investment-platform workflows.
  • Knowledge of side-letter requirements, ILPA reporting standards, and related reporting considerations.
  • Experience with data pipelines, metadata management, data dictionaries, and automated data-quality checks.

Cloud Technologies

Essential

  • Understanding of cloud-based data, analytics, and reporting environments.
  • Ability to work with controlled access, data protection, reporting environments, and managed analytical services.

Preferred

  • Familiarity with Azure or Microsoft Fabric.
  • Experience with semantic models, cloud data platforms, analytical workspaces, and reporting deployment pipelines.
  • Exposure to cloud-based workflow automation and scheduled reporting.
  • Understanding of resource-efficient data processing and sustainable reporting operations.

Frameworks and Libraries

Essential

  • Excel reporting and analytical capabilities, including Power Query.
  • Power BI reporting, visualization, and dashboard capabilities where applicable.
  • SQL querying and data-analysis tools.
  • Financial and investment-performance calculation methodologies.
  • Reporting and reconciliation frameworks that support recurring investor and portfolio outputs.

Preferred

  • Python data-analysis libraries and automation frameworks.
  • Semantic modelling and reporting frameworks.
  • Tools supporting data-quality monitoring, workflow automation, and report validation.
  • Investor-platform or eFront-style workflows.
  • Tools and processes aligned with ILPA reporting standards.

Development Tools and Methodologies

Essential

  • Experience across the reporting lifecycle, including requirements analysis, data review, calculation, validation, stakeholder review, delivery, and issue resolution.
  • Strong Excel-based analytical and reporting practices.
  • Experience using SQL and/or Power BI for portfolio reporting and analysis.
  • Ability to document requirements, calculation methodologies, validation procedures, reporting controls, and operational processes.
  • Familiarity with structured workstream ownership, issue tracking, review cycles, and delivery management.
  • Understanding of Agile, iterative delivery, or controlled reporting-development practices.

Preferred

  • Experience with Jira and Confluence for work-item tracking, documentation, and team collaboration.
  • Experience with deployment pipelines for reporting, data, or semantic-model changes.
  • Familiarity with Python-based automation, scheduled workflows, and repeatable reporting processes.
  • Exposure to prompt engineering with approved GenAI tools for controlled analytical and documentation activities.
  • Experience improving reporting efficiency through automation, standardization, and reusable templates.

Security Protocols

Essential

  • Understanding of confidentiality, access control, data protection, and appropriate handling of investment and investor information.
  • Ability to apply role-based access, controlled sharing, secure storage, and approved data-use practices.
  • Understanding of data validation, auditability, change control, and reporting governance.
  • Ability to identify and escalate data-quality, privacy, calculation, or reporting risks.
  • Ability to use approved GenAI tools without exposing restricted, confidential, or sensitive information.

Preferred

  • Familiarity with financial-services risk, compliance, and audit requirements.
  • Experience supporting evidence collection, control testing, reporting reviews, and issue remediation.
  • Knowledge of secure cloud analytics and reporting environments.
  • Familiarity with data masking, retention, access reviews, and usage monitoring.


Experience Requirements

  • Overall experience: Minimum 5 years of experience in asset management, investment banking, fund administration, financial services, or a related analytical reporting role.
  • Domain experience: Exposure to private credit, private equity, investment reporting, portfolio analytics, alternative investments, or recurring investor-reporting workflows.
  • Performance experience: Strong knowledge of TWR, MWR, IRR, MOIC, TVPI, DPI, and RVPI, along with exposure, attribution, benchmark, and investor-reporting outputs.
  • Technical experience: Strong Excel skills, including formulas, pivot tables, lookups, Power Query, and data validation; experience with SQL and/or Power BI.
  • Reporting experience: Ability to own reporting workstreams, validate results, identify exceptions, explain calculations, and deliver accurate outputs within agreed timelines.
  • Preferred experience: Python for data analysis or automation, approved GenAI prompt engineering, Azure or Microsoft Fabric, semantic models, deployment pipelines, alternative-investment accounting concepts, side letters, ILPA reporting standards, and Jira or Confluence.
  • Industry preference: Experience supporting investment management, alternative investments, fund operations, portfolio reporting, or regulated financial-services processes is preferred.
  • Alternative experience pathways: Equivalent combinations of relevant professional experience, technical training, analytical delivery, investment-reporting projects, or demonstrable portfolio-analysis work may be considered.
  • Outcome evidence: Candidates should demonstrate contributions to improved reporting accuracy, reduced manual effort, stronger data controls, timely delivery, enhanced portfolio insight, or more efficient reporting processes.


Day-to-Day Activities

  • Analyze portfolio, investment, exposure, performance, attribution, benchmark, and investor-reporting data using Excel, SQL, Power BI, and related tools.
  • Collaborate with investment, finance, operations, fund administration, technology, risk, and reporting stakeholders through planning meetings, review sessions, issue discussions, and delivery checkpoints.
  • Deliver validated reports, dashboards, analytical outputs, reconciliations, data-quality checks, calculation documentation, and process improvements.
  • Own assigned workstreams, make evidence-based recommendations within the defined scope, and escalate risks related to data accuracy, reporting deadlines, controls, and stakeholder requirements.


Qualifications

  • Bachelor’s degree in Finance, Accounting, Economics, Computer Science, Data Analytics, Business, or a related field is required; equivalent relevant experience may be considered.
  • Minimum 5 years of experience in asset management, investment banking, fund administration, financial services, or a related investment-reporting environment.
  • Demonstrated knowledge of alternative-investment performance metrics, portfolio exposure attributes, investor reporting, Excel, and SQL and/or Power BI.
  • CFA, FRM, CAIA, CIPM, Chartered Accountant, or other industry-relevant professional credentials are strongly preferred.
  • Commitment to continuous professional development in alternative investments, performance measurement, reporting standards, data analytics, automation, responsible GenAI use, and financial-services practices.


Professional Competencies

  • Applies structured analytical thinking to interpret investment data, validate performance calculations, investigate exceptions, and identify reporting risks.
  • Owns assigned workstreams, coordinates dependencies, and contributes effectively to cross-functional delivery with limited supervision where appropriate.
  • Communicates complex data, performance results, assumptions, risks, and recommendations clearly in written and verbal formats.
  • Adapts to changing reporting requirements, investment structures, data sources, technology platforms, standards, and stakeholder priorities.
  • Identifies practical opportunities to improve reporting accuracy, automation, data quality, transparency, efficiency, and sustainable use of resources.
  • Manages time and priorities effectively across recurring reporting deadlines, analysis requests, issue resolution, documentation, reviews, and process-improvement activities.


S​YNECHRON’S DIVERSITY & INCLUSION STATEMENT
 

Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.


All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

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About Synechron

At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering , servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our FinLabs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 2

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