Manager, Analyst Services

About Solovis

Solovis is a leading portfolio management and analytics platform helping institutional investors navigate today's complex global markets with clarity and confidence. Backed by Insight Partners, we're building the next chapter of growth by investing in people and product to raise the bar on quality and client outcomes. Our team is driven by a culture of disciplined execution, humility, and curiosity where AI is at the core of how we operate, innovate, and serve clients. At Solovis, you'll join a tech-forward, growth-minded team that believes in learning fast, thinking big, and delivering meaningful impact for asset owners worldwide. Our companies are not the largest or flashiest, but they are among the best-run software businesses, creating value for customers and shareholders at an accelerated pace.

About the role

As an Analyst Services Manager, you will lead one of the core operational teams responsible for delivering accurate, timely investment data to clients through a structured, SLA-driven pipeline. Depending on team assignment, your scope will center on either the intake and routing of investment data into the platform, or the extraction, mapping, and enrichment of that data for downstream delivery.

This is a hands-on leadership role. You will manage a team of data analysts while personally driving the automation, process discipline, and quality standards that keep the pipeline running. You are expected to leverage AI tools and automation to reduce manual touchpoints, increase straight-through processing rates, and continuously improve throughput and reliability.

This role is ideal for a technically fluent people leader who is detail-oriented, data-driven, and committed to building scalable, automation-first operations in a structured, high-accountability environment.

Key Responsibilities

• Lead, develop, and hold accountable a team of Analyst Services professionals responsible for executing against defined SLAs, quality targets, and throughput goals
• Drive disciplined execution within your team by establishing clear workflows, enforcing process boundaries, and ensuring work is completed accurately and on time
• Design, build, and maintain automation for core workflows using tools such as Alteryx, Power Automate, Python, and internal platforms to reduce manual effort and increase straight-through processing
• Manage document retrieval pipelines, data feed integrations, API connections, and automated failure notifications to ensure reliable data intake across all client portfolios
• Own and execute extraction, mapping, enrichment, and QA/QC processes for investment data across public, private, and operational asset classes
• Define, track, and report on team KPIs including SLA adherence, processing accuracy, integration uptime, automation coverage, and cycle time
• Recruit, onboard, and cross-train team members to build a resilient bench that reduces single points of failure and supports peak-period workload flexibility
• Partner with peer managers across Data Operations, Data Processing, and Client Delivery to maintain feedback loops, enforce handoff discipline, and resolve cross-team issues
• Coordinate with Professional Services on new fund and client onboarding to ensure intake configurations, extraction templates, and processing workflows are properly established
• Identify and implement process improvements that eliminate recurring errors, reduce rework, and improve the end-to-end data pipeline

Competencies

• Disciplined Execution & Accountability – Drives rigorous adherence to SLAs, KPIs, and quality standards. Holds themselves and the team to clear expectations and follows through on commitments without exception
• Team Development & Coaching – Builds, mentors, and retains high-performing teams through regular feedback, individual growth planning, and creating an environment where people do their best work
• Process Improvement Mindset – Continuously identifies inefficiencies and drives automation-first solutions to reduce manual effort, eliminate rework, and increase throughput
• Cross-Functional Collaboration – Partners effectively across teams to ensure seamless handoffs, shared accountability, and clear feedback loops that prevent issues from cascading downstream
• Data-Driven Decision Making – Uses metrics, dashboards, and operational data to prioritize work, allocate resources, and measure team performance objectively
• Change Management & Adaptability – Navigates shifting priorities, new tooling, and evolving client needs while maintaining team stability, morale, and execution quality
• Root Cause Problem Solving – Diagnoses systemic issues at the pipeline or process level and implements durable fixes rather than reactive patches
• Clear & Concise Communication – Translates complex technical and operational topics into plain language for stakeholders at all levels, from analysts to senior leadership

Skills

• Workflow Automation & Orchestration – Hands-on experience designing and maintaining automated pipelines using tools such as Alteryx, Power Automate, or similar platforms
• Data Integration & Pipeline Management – Practical knowledge of managing data feeds, API connections, file transfer protocols, and monitoring integration health across multiple sources
• Data Extraction, Mapping & Enrichment – Understanding of financial data extraction workflows, mapping logic, data structuring, and enrichment processes across public, private, and operational asset classes.
• Document Management & Classification – Familiarity with document intake patterns, metadata tagging frameworks, and routing logic within a data operations context
• KPI & SLA Management – Experience defining, tracking, and reporting on operational metrics such as SLA adherence, processing accuracy, cycle time, and automation coverage
• AI & Intelligent Automation Fluency – Familiarity with leveraging AI tools (OCR, NLP, classification models) to accelerate document processing and reduce manual touchpoints
• Team Capacity Planning & Resource Allocation – Ability to forecast workload, manage staffing across queues and peak periods, and cross-train to eliminate single points of failure.
• Investment Data Domain Knowledge – Familiarity with portfolio analytics, financial statements, fund structures, or investment operations workflows. Direct experience in asset management or fund administration is a plus