Engagement Manager, Data Science

About Us

TheMathCompany (MathCo) is a global Enterprise AI and Analytics company trusted by leading Fortune 500 and Global 2000 enterprises for data-driven decision-making. Founded in 2016, MathCo builds custom AI and advanced analytics solutions that solve complex business challenges through our innovative hybrid model. NucliOS, MathCo's proprietary platform, enables connected intelligence at a lower total cost of ownership (TCO).

At MathCo, we foster an open, transparent, and collaborative culture. We value capability and attitude over tenure, offering exciting growth opportunities that empower our Mathemagicians to
Leave a Mark
.

Role Description

We are seeking an
Engagement Manager
with deep technical grounding in
Recommender Systems and Personalization
to lead complex, high-impact engagements with enterprise clients in the retail and e-commerce domain.

This role combines client leadership, delivery ownership, and hands-on analytics expertise. You'll partner with business and data science teams to define the recommendation strategy, design and operationalize AI-driven personalization systems, and ensure measurable business outcomes.

The ideal candidate is fluent in both
client engagement and machine learning
, capable of translating recommendation models (BERT, NCF, content-based, and collaborative filtering) into actionable business value.

Key Responsibilities

• Own the client relationship and act as the strategic interface between MathCo and senior stakeholders at large retail or e-commerce enterprises.
• Lead the end-to-end delivery of recommendation system projects — from problem framing and modeling approach to deployment and performance optimization.
• Oversee technical discussions on
  model architecture, feature engineering, loss/activation functions, and evaluation metrics (e.g., NDCG, MAP)
  .
• Translate analytical outcomes into clear, data-backed recommendations that influence business strategy and drive measurable impact.
• Collaborate closely with cross-functional teams (Data Engineering, MLOps, and Product) to operationalize recommender systems using modern AI tech stacks (TensorFlow, PyTorch, BERT, NCF).
• Build and mentor a team of data scientists and machine learning engineers, ensuring best practices in project management, technical quality, and client communication.
• Identify business development opportunities within existing engagements and support pre-sales discussions with prospective clients.

Skills Required

• Strong hands-on understanding of
  recommender systems
  , personalization algorithms, and ranking models.
• Deep familiarity with
  BERT, NCF, neural network architectures
  , and feature embedding methods.
• Proficiency in
  Python
  , with experience in
  TensorFlow / PyTorch
  frameworks.
• Working knowledge of
  data pipelines, feature stores, and MLOps practices
  .
• Excellent client-facing skills: can communicate complex technical solutions in a clear and business-relevant way.
• Ability to lead analytical engagements, align multiple stakeholders, and manage delivery timelines in dynamic environments.
• High comfort level with ambiguity and change, with a focus on problem-solving and measurable results.

Education / Qualification

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related quantitative discipline.
• Master's in Business Analytics, Data Science, or equivalent is preferred.
• Consulting experience in AI/ML or advanced analytics is highly desirable.

Experience

• 6–10 years of total experience, including at least 3–4 years in machine learning or recommender systems projects.
• Proven track record managing analytics or AI engagements for large retail, e-commerce, or consumer brands (e.g., Amazon, Walmart, Target, Wayfair, Instacart, eBay, DoorDash, etc.).

Being a Mathemagician

• Embody MathCo's culture of ownership, transparency, and excellence.
• Demonstrate curiosity and initiative in solving client problems through data.
• Coach and inspire your team to deliver exceptional impact.
• Foster diversity of thought and collaboration across teams.