Open-End Fund Analytics Specialist – Performance, Attribution, Python & SQL

Job Summary

Synechron is seeking an Analytics – Open-End Fund professional with expertise in performance and attribution reporting, portfolio exposure monitoring, alternative investments, and data analytics.

The role will support the analysis and reporting of open-end fund portfolios, including performance results, attribution, risk metrics, portfolio characteristics, and exposure information. The position will combine investment knowledge with practical experience in Python, SQL, and data visualization tools such as Power BI.

This role will contribute to business objectives by improving reporting accuracy, strengthening portfolio insight, supporting investment decision-making, and delivering clear and timely analytics to cross-functional stakeholders.

Software Requirements

Required Software Skills

• Python, SQL, and/or data visualization tools: At least 3 years of working proficiency using one or more of these technologies to support data analysis and reporting.
• Python: Experience preparing, transforming, analyzing, validating, or automating investment and portfolio data.
• SQL: Experience querying, joining, validating, and analyzing structured investment and portfolio datasets.
• Data visualization: Experience using Power BI or an equivalent tool to create dashboards, reports, visualizations, and analytical outputs.
• Performance reporting tools: Experience supporting investment performance reporting and related analytical workflows.
• Attribution reporting tools: Experience supporting performance attribution analysis and reporting.
• Project management tools: Basic familiarity with Jira, Confluence, or equivalent tools is preferred.

Preferred Software Skills

• Experience using more than one of Python, SQL, and Power BI.
• Familiarity with data models, reporting automation, data validation, and repeatable analytical workflows.
• Exposure to project-management, documentation, and collaboration tools such as Jira and Confluence.
• Familiarity with tools used for risk reporting, portfolio analytics, investment data management, and reporting controls.

Version and Experience Guidance

• Specific software versions are not mandated in the requirements.
• Candidates should have experience with current, production-supported versions of Python, SQL, Power BI, and related analytics tools.
• Candidates should be able to validate data, document calculation logic, manage reporting changes, and maintain reproducible analytical outputs.
• The required technology experience should be applied to investment, portfolio, performance, attribution, or related financial analysis.

Overall Responsibilities

• Prepare, analyze, validate, and maintain performance and attribution reporting for open-end fund portfolios.
• Monitor portfolio exposures and analyze portfolio characteristics across relevant investment strategies.
• Produce and review performance reporting, risk metrics, portfolio analytics, and related investment-reporting outputs.
• Apply knowledge of open-end fund structures to interpret portfolio data, fund activity, exposure information, and reporting requirements.
• Use Python, SQL, Power BI, and related tools to extract, transform, analyze, reconcile, and visualize investment data.
• Investigate data quality issues, reporting exceptions, calculation differences, and inconsistencies in portfolio analytics.
• Support the development and enhancement of dashboards, analytical models, reporting templates, and repeatable reporting processes.
• Collaborate with investment, risk, operations, finance, technology, and reporting teams to clarify requirements and resolve issues.
• Translate complex investment information into clear analysis for technical and non-technical stakeholders.
• Maintain documentation covering data sources, calculation methodologies, reporting definitions, validation procedures, and process controls.
• Support process improvement, reporting standardization, automation, and efficient use of analytical resources.
• Ensure reporting outputs are accurate, timely, consistent, traceable, and aligned with applicable governance standards.
• Contribute to measurable outcomes such as improved reporting quality, reduced manual effort, stronger data controls, and timely delivery of portfolio insights.

Technical Skills (By Category)

Programming Languages

Essential

• At least 3 years of working proficiency in Python, SQL, and/or data visualization tools.
• Ability to use Python for data preparation, analysis, validation, reporting, and workflow automation.
• Ability to use SQL for data extraction, transformation, reconciliation, and analysis.
• Ability to document analytical logic, calculations, assumptions, and data dependencies.

Preferred

• Experience using both Python and SQL for investment data analysis.
• Experience developing reusable scripts, analytical utilities, or automated reporting processes.
• Familiarity with programming practices that support testing, validation, reproducibility, and controlled deployment.

Databases/Data Management

Essential

• Experience working with structured investment, portfolio, fund, performance, attribution, and risk data.
• Understanding of portfolio exposure attributes and portfolio characteristics.
• Ability to perform data completeness, accuracy, consistency, reconciliation, and reasonableness checks.
• Understanding of data lineage, source-to-report mapping, data definitions, and reporting controls.
• Ability to maintain data quality and integrity across recurring analytics and reporting processes.

Preferred

• Experience with data warehouses, analytical data models, semantic models, or data marts.
• Familiarity with alternative-investment data structures and reporting outputs.
• Experience with data pipelines, data dictionaries, metadata management, and automated data-quality checks.
• Exposure to data governance, retention, and lifecycle management practices.

Cloud Technologies

Essential

• Understanding of technology environments used for investment analytics, reporting, data management, and visualization.
• Ability to work with controlled data access, reporting environments, and managed analytical services.

Preferred

• Exposure to cloud-based data, analytics, and reporting platforms.
• Familiarity with cloud data warehouses, semantic models, and reporting deployment processes.
• Understanding of resource-efficient data processing and sustainable reporting operations.

Frameworks and Libraries

Essential

• Python-based data analysis and reporting capabilities.
• SQL querying and analytical capabilities.
• Power BI or an equivalent data visualization and reporting platform.
• Performance reporting and attribution analysis methodologies.
• Portfolio exposure monitoring and risk-reporting frameworks.
• Tools and processes supporting data reconciliation, validation, and reporting controls.

Preferred

• Python libraries used for data manipulation, analysis, visualization, and automation.
• Power BI data modelling, dashboard development, calculated measures, and report distribution.
• Tools supporting portfolio analytics, investment data workflows, and recurring reporting automation.
• Frameworks supporting data quality, exception management, and analytical model validation.

Development Tools and Methodologies

Essential

• Experience across the analytics and reporting lifecycle, including requirements analysis, data review, calculation, validation, stakeholder review, delivery, and issue resolution.
• Experience using Python, SQL, and/or Power BI to support data analysis and reporting.
• Ability to create reporting specifications, data mappings, calculation documentation, validation procedures, and operational process documents.
• Familiarity with structured workstream ownership, review cycles, issue tracking, and delivery management.
• Ability to investigate reporting issues, identify root causes, and implement corrective actions.
• Understanding of controlled reporting, change management, quality review, and governance practices.

Preferred

• Basic familiarity with Jira, Confluence, or equivalent project-management and documentation tools.
• Experience with reporting automation, repeatable workflows, and scheduled analytical processes.
• Familiarity with Agile or iterative delivery practices.
• Experience improving reporting processes through standardization, automation, and reusable templates.

Security Protocols

Essential

• Understanding of confidentiality, access control, data protection, and appropriate handling of fund and portfolio information.
• Ability to apply controlled data access, secure sharing, approved storage, and reporting governance practices.
• Understanding of auditability, change control, data validation, and traceability.
• Ability to identify and escalate data-quality, calculation, privacy, access, and reporting risks.
• Ability to follow applicable information-security, privacy, and organizational standards.

Preferred

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

Experience Requirements

• Overall experience: Minimum 5 years of experience at an asset management firm, investment bank, financial services organization, or a related investment analytics environment.
• Performance and attribution experience: Solid knowledge of performance and attribution reporting.
• Fund experience: Solid understanding of open-end fund structures, including portfolio exposure monitoring.
• Investment experience: Strong knowledge of alternative investments and related reporting outputs, including performance reporting, risk metrics, and portfolio characteristics.
• Technical experience: At least 3 years of experience using Python, SQL, and/or data visualization tools such as Power BI for data analysis and reporting.
• Credential requirement: CFA or CIPM candidacy with at least one exam level passed.
• Communication experience: Demonstrated ability to communicate investment analysis clearly and work effectively across functions.
• Preferred experience: Basic familiarity with Jira, Confluence, project management, reporting automation, data governance, and analytical workflow improvement.
• Industry preference: Experience supporting portfolio analytics, investment performance, fund reporting, risk reporting, or alternative-investment operations is preferred.
• Alternative experience pathways: Equivalent combinations of relevant investment analytics experience, professional training, demonstrated reporting delivery, technical projects, or validated portfolio-analysis work may be considered where they meet the required capabilities.

Day-to-Day Activities

• Analyze open-end fund performance, attribution, portfolio exposures, risk metrics, portfolio characteristics, and related investment-reporting data using Python, SQL, Power BI, and other approved tools.
• Collaborate with investment, risk, operations, finance, technology, and reporting teams through requirements discussions, review meetings, issue-resolution sessions, and delivery checkpoints.
• Deliver validated reports, dashboards, analytical outputs, data reconciliations, performance analysis, documentation, and reporting-process improvements.
• Own assigned workstreams, make evidence-based recommendations within the defined scope, and escalate risks related to data quality, calculation accuracy, reporting deadlines, and stakeholder requirements.

Qualifications

• Bachelor’s degree in Finance, Accounting, Economics, or a related field is required; equivalent relevant experience may be considered.
• CFA or CIPM candidacy with at least one exam level passed is required; CA designation, CFA designation, CA Inter qualification, and/or an MBA with a Finance focus is preferred.
• Minimum 5 years of experience in asset management, investment banking, financial services, investment analytics, or a related reporting environment.
• At least 3 years of experience using Python, SQL, and/or data visualization tools such as Power BI to support investment data analysis and reporting.
• Commitment to continuous professional development in performance measurement, attribution, alternative investments, portfolio analytics, data analysis, reporting standards, and responsible use of technology.

Professional Competencies

• Applies structured analytical thinking to interpret investment data, evaluate performance and attribution results, validate calculations, and investigate reporting exceptions.
• Works effectively across investment, risk, operations, finance, technology, and reporting teams while owning assigned deliverables and dependencies.
• Communicates complex investment analytics, assumptions, data limitations, risks, and recommendations clearly in written and verbal formats.
• Adapts to changing fund structures, reporting requirements, data sources, analytical tools, stakeholder priorities, and market conditions through continuous learning.
• Identifies practical opportunities to improve reporting accuracy, automation, data quality, transparency, efficiency, and sustainable use of analytical resources.
• Manages time and priorities effectively across recurring reporting deadlines, analysis requests, data validation, issue resolution, documentation, and process improvement.

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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