Data Science Director

Data Analytics Full-Time ALL USA, United States ReqID:5148


Envestnet is seeking a passionate and talented Data Science Director to join our team. This position is a remote role.

Envestnet is transforming the way financial advice and wellness are delivered. Our mission is to empower advisors and financial service providers with innovative technology, solutions, and intelligence to make financial wellness a reality for everyone.

Since our founding 20 years ago, we are fully vested in helping people live an intelligent financial life. If you love the idea of working in a Fintech company with the environment and excitement of a start-up where you are making everyday impact - then read on. 

Job Summary:   

Envestnet Data & Analytics is driving innovations using the latest Machine Learning algorithms and Big Data Engineering frameworks at Envestnet. We have a high-caliber, focused and a mission-driven culture for our teams. Data Science work is challenging and rewarding as the Machine Learning models, we build have to meet accuracy SLAs, be scalable to run on petabytes of data and parallelizable to run on distributed computing infrastructure. The insights we derive from the financial data matters to crucial cutting-edge business decisions made across the global financial services firms every day and solves real world problems. We are leveraging our deep expertise in financial data to launch innovative solutions into the Financial Services Industry.

Job Responsibilities:

  • Identify opportunities to solve client problems of scale using voluminous transaction data
  • Generate optimal solutions that will be work in production within defined constraints of cost, time, quality
  • Lead cross functional teams to solve complex problems and create scalable models/algorithms that will be integrated into Envestnet’s tools and products.
  • Communicate context, data, solution and implications to the team, senior leadership and stakeholders
  • Lead and guide junior data scientists to deliver results
  • Collaborate cross-functionally with other teams such as the Engineering team, Business Analytics team and Validation team.
  • Own delivery of specific models and products with embedded analytics solutions
  • Continuously improve models in production while leveraging new techniques and technology
  • Encourage a culture of innovation within the organization
  • Adherence to and application of Envestnet legal, compliance, risk, business continuity and administrative policy within the role and department(s) including the timely completion of training & awareness, affirmations and testing as requested.
  • As part of the responsibilities for this role, you will understand and readily support Envestnet's established corporate business practices, policies, internal controls and procedures designed to create value or minimize risk

Required Qualifications:

  • 12+ years of experience in the area of data science/machine learning specializing in a relevant field such as Probability, Statistics, Machine Learning, Data Mining, Artificial intelligence/Computer Science.
  • Experience in building and operationalizing solutions with embedded models in production to solve real world program
  • Solid programming skills in Python, ML frameworks (e.g., scikit-learn, tensorflow, nltk, sagemaker), Shell Programming and SQL.
  • Deep understanding of statistical modelling/machine learning/ data mining concepts
  • Strong analytical and quantitative problem-solving ability
  • Strong interpersonal and communication skills: ability to tell a clear, concise, actionable story with data, to folks across various levels of the company.
  • Strong stakeholder management skills to work with both internal and external clients through out a solution development lifecycle
  • Excellent team management skills – Have the technical depth to work with junior data scientists while having the ability to zoom out and set aspirational objectives for the team
  • Cross functional leadership: Comfort in leading teams drawn from multiple teams of data science, engineering, operations, business analytics to deliver on a project end-to-end
  • Experience in working with huge datasets and big data technologies.
  • Experience with Natural Language Processing/Text Analytics 

Preferred Qualifications:

  • Graduate (preferred) degree in Data Science/Computer Science/ Mathematics/ Statistics or MBA Data Science
  • Experience in any one of the following industries: Wealth Management, Retail and Banking industries.
  • Experience with AWS based technology stack and delivering API based solutions

About Us:

Envestnet is a leading independent provider of technology‐enabled investment and practice management solutions to financial advisors who are independent, as well as those who are associated with small or mid‐sized financial advisory firms and larger financial institutions. Envestnet's technology is focused on addressing financial advisors' front, middle, and back‐office needs while leveraging our platform to grow their businesses and expand client relationships.

We offer a highly competitive compensation and benefits package as well as the excitement, challenges, and rewards of a fast-growing, entrepreneurial company.

Why Choose Envestnet:

  • Be a member of a leading financial services and products innovation company
  • Competitive Compensation/Total Reward Packages that include:
    • Health Benefits (Health/Dental/Vision)
    • Paid Time Off (PTO) & Volunteer Time Off (VTO)
    • 401K – Company Match
    • Annual Bonus Incentives
    • Equity
    • Parental Stipend
    • Tuition Reimbursement
    • Student Debt Program
    • Charitable match
    • Wellness Program
  • Work on global projects with diverse, energetic, team members who respect each other and celebrate differences
  • The best work locations with unlimited snacks!


The annual base salary range for this position is $93,000 to $210,000.

Envestnet is an Equal Opportunity Employer.

Envestnet refers to the family of operating subsidiaries of the public holding company, Envestnet, Inc. (NYSE: ENV).