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Medalogix

Vice President of Data Science

Reposted 15 Days Ago
Remote
2 Locations
Senior level
Remote
2 Locations
Senior level
The VP of Data Science leads a team to deliver data-driven solutions, drives innovation, and partners cross-functionally to achieve strategic goals.
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Description

This VP of Data Search is being represented exclusively by JM Search. Interested Parties should send a resume to:

Ryan Gilligan: [email protected]

Medalogix is at a pivotal point in the company’s history. The company has experienced significant growth over the past few years. The Vice President, Data Science will be responsible for the delivery of data science solutions (statistical, machine learning, GenAI) as part of Medalogix’s product offerings. This person will be responsible for managing a team of data scientists and machine learning engineers. This leader must be highly knowledgeable about Medalogix’s business and the dynamic environment in which it operates, so that s/he can effectively ensure that the organization consistently maintains an appropriate balance between its entrepreneurial culture while sustaining a robust data science and artificial intelligence agenda.

Key Functions & Responsibilities:

• Responsible for leading the Data Science team which is a critical backbone and core component of the Medalogix suite of product offerings.

• Owning delivery of data science solutions (statistical, machine learning, GenAI) as part of product offerings.

• Driving the continued adoption of GenAI intelligence and broader Medalogix agenda.

• Injecting innovation into Data Science team. Creating a culture that fosters innovation and allows for risk taking to solve ambiguous problems.

• Leverage open-source technologies to drive continued adoption of GenAI, NLP, and ML models.

• Partner with broader IT teams and business stakeholders. Sharing ownership in the continued customer adoption and growth objectives.

Year One Critical Success Factors:

• Quickly build effective relationships with team members and business partners while acclimating to a highly collaborative company culture.

• Gain detailed and in-depth knowledge of current product offerings and strategy around future product offerings.

• Identify opportunities for innovation by leveraging emerging data science related technologies and trends.

• Assess structure and skillset of current team. Identify gaps and create roadmap to mitigate potential gaps.

Requirements

• Leadership – ability to lead the team in combination with bringing data science excellence. Proven experience in managing AI application implementation projects, preferably in a SaaS oriented company.

• Innovation – track record in creating new analytics adopted in production operations; specific focus on ground-up innovation and methods involved to take an idea to reality.

• Measurement – deep acumen and experience in measuring solution effectiveness. Able to articulate processes/skills necessary in variety of use cases.

• Technology – reasonably deep technical skills that can be used to effectively manage technical team members. Experience with NLP (similar practices to using GenAI) in solving real use case at scale. Strong understanding of AI technologies, machine learning, and data analytics.

• Bachelor's degree in a relevant field (computer science, information systems, etc.)

• Advanced degree or certifications in AI, data science, deep tech or related areas is a plus.

• Ability to deal with a level of ambiguity while driving towards business outcomes.

Benefits

• Highly sponsored and a variety of Healthcare Plans (PPO, HSA, and FSA)

• Dental and Vision Insurance

• Immediate vesting in the 401(k) with Company Match

• Maternity/Paternity Leave

• Celebration of 'Wins' with Team Outings and Events

• Generous Paid Time Off with an additional (8 Paid Holidays, Floating Holiday, and Company Sponsored Volunteering Holiday)

• Free Downtown Parking (When applicable)

• Referral Bonus Opportunity

Top Skills

Data Science Solutions
Genai
Machine Learning
Natural Language Processing
Open-Source Technologies
Statistical Analysis

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