Senior Data Scientist
Content + Source + Freshness • 12 Dec 2025 • 95% confidence
Offer value
Moderate score due to solid organizational growth, competitive skill development, and the increasing demand for data-driven solutions.
- Engage in impactful data science initiatives within supply chains.
- Opportunity to leverage ML tools for enhanced decision making.
- Candidates must possess 3-6 years of relevant data experience.
Pros
- Growing importance of data science in supply chain operations.
- Engagement with cutting-edge ML and forecasting tools.
- Opportunity for impactful work within a rapidly scaling company.
Cons
- Mid-level experience required may deter some candidates.
- Potential challenges in adapting to evolving tech environments.
- Dependency on collaboration with varied teams may be demanding.
Who it's for
Mid-Level • Hybrid / telecommute options likely.
Good fit
- Data scientists seeking growth in the supply chain domain.
- Professionals eager to innovate with AI and analytics.
- Individuals passionate about real-world applications of data.
Not recommended for
- Entry-level candidates without relevant qualifications.
- Individuals seeking roles with minimal collaboration.
- Professionals unfamiliar with Python and ML methods.
Motivation fit
Key skills
About the job
About the Company
Why We Built Lyric: Supply chains are more critical and complex than ever. Every day, large enterprises navigate trillions of possible decisions that could impact the bottom line. Powerful algorithms and AI can address these problems, yet most organizations struggle to leverage supply chain AI at scale. The current SCM technologies are either rigid, limited-scope point solutions or custom solutions built in-house, which demand immense expertise and investment.
That is…until now.
Enter Lyric: Lyric is an enterprise AI platform built specifically for supply chains, offering the best of both worlds:
Out-of-the-box AI solutions for optimizing networks, allocating inventory, scheduling routes, planning fulfillment capacity, promising orders, propagating demand, building predictions, analyzing scenarios, and more, plus
A platform-first approach that empowers both business and technical users with end-to-end product composability, leveraging no-code tools, their own code, or even forking our code to build and refine supply chain decision intelligence
With Lyric, enterprises no longer have to choose between flexibility and speed—they get both.
The Mission: We’re building a new era in supply chain with the team best equipped to lead it. With over 20 years at the intersection of supply chain and algorithms, we developed a deep conviction that global supply chains needed something like Lyric. Since our inception in December 2021, that conviction has been validated time and time again.
Today, a growing number of Fortune 500 companies, including Smurfit WestRock, Estée Lauder, Coca-Cola, Nike, and more, are innovating on their own terms with Lyric. We can’t wait to see what our customers, both current and future, are empowered to build with us next. Come build with us!
Position Overview:
We’re hiring a Sr Data Scientist to propel Lyric’s Predictions workspace — a no-code interface that lets users build predictive models for supply chain problem solving. You’ll work closely with Customer Success to ensure that the ML and Forecasting workspaces have adequate and forward looking algorithmic capabilities to propel and scale supply chain business problem solving.
Key Responsibilities:
Stay current with respect to new analytical methods in the area of predictive analytics, to maintain proficiency in applying new and varied methods, and to be competent in justifying methods selected.
Conduct quick proof-of-concept experiments to prove the viability of algorithms and techniques with regards to fitment within the machine learning and demand forecasting workspaces.
Ownership of MLOps and functional QA of the ML workspaces.
Must-Haves:
3–6 YOE in product roles
Deep fundamental understanding of statistical models, machine learning, and deep learning
Strong experience with time series forecasting
Solid Python programming background
