Data Scientist

Our employees are our most valuable asset.

Below covers everything you need to know about what this opportunity entails, as well as what is expected from applicants.

Job Description

ABOUT THE TEAM :

Virtus employs a comprehensive, dedicated multi-market and multi-channel distribution approach to access the broadest base of potential clients in the U.

S. and select markets in Europe, Asia, and Australia. Experienced, channelized sales teams cultivate deep, diverse, and enduring relationships with financial advisers, consultants, and institutional and individual clients, supported by a centralized sales desk and associated functions including :

• National Accounts, which manages retail product availability and platform placement to deepen relationships with distribution partners, and Institutional Consultant Relations, which represents strategies and investment performance of affiliated managers with consultants who are gatekeepers to largest percentage of institutional clients.
• Marketing, which is tasked with differentiating our retail presence through one-point access to specialized managers and helping financial advisors build their practices using thoughtful market education to help clients achieve better outcomes.
• Dedicated support staff in business intelligence, RFP / database management, digital marketing, and creative services.

Job Summary

We are looking for a Data Scientist to support our distribution efforts across all channels. The Distribution Intelligence team provides advanced analytics, dashboards, and reporting to help inform strategic distribution decisions and ultimately increase sales.

This role will enable and execute data strategy and integration (both internal and third party) to deliver data to our sales and sales leadership teams in a meaningful and actionable way.

The Data Scientist will apply statistical theory and methods to collect, interpret, and summarize data as well as make predictions and recommend actions based on data.

The ideal candidate is a solutions-oriented leader, comfortable with ambiguity and excited to chart a course of data delivery that will have a measurable business impact.

Essential Duties & Responsibilities

• Build predictive models and machine-learning algorithms.
• Design and build the infrastructure and systems that support data collection, storage, and analysis.
• Identify and analyze business problems and opportunities, conduct statistical analyses, and propose solutions to business challenges.
• Develop solutions to improve business processes, accuracy, and performance.
• Present information using data visualization techniques in a way that is easy for non-technical stakeholders to understand.

Document all processes and research.

Specific Qualifications

• Bachelor’s degree in computer science, statistics, applied math or related field required. Master’s degree preferred.
• Extensive background in data mining and statistical analysis.
• 1-3 years’ experience in a data-related field developing analytical strategies, business intelligence capabilities, and overall data-driven decision-making roadmap development.
• 2+ years’ experience in a data-related field developing analytical strategies, business intelligence capabilities, and overall data-driven decision-making roadmap development.
• Expertise with data visualization tools such as PowerBI.
• Experience using business intelligence tools and data frameworks.
• Background in retail distribution in the asset management industry and associated third-party data sources :
• DST Walletshare
• Firm Data Packs
• Envestnet
• Discovery
• Broadridge
• Excellent verbal and written communication skills.
• Excellent organizational skills and attention to detail.
• Able to multitask, prioritize, and manage time effectively.
• Strong math skills.
• Problem-solving aptitude.
• Relentless intellectual curiosity and a drive to excel at the highest level.

Salary Range : $115,000- $140,000

The starting salary offer will vary based on the applicant’s education, experience, skills, abilities, geographic location, internal equity, and alignment with market data.

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