Senior Full Stack Data Scientist - Remote US

Reposted 23 Days Ago
29 Locations
Remote
130K-180K
Senior level
Artificial Intelligence • Fashion • Software
The Role
Lead development of forecasting algorithms, collaborate on greenfield projects, and enhance forecast accuracy using customer data signals in a dynamic team environment.
Summary Generated by Built In
About Syrup

🌍 In a world with deep supply chain disruptions, true omni-channel networks, and sustainability-minded consumers, there is a need for next-generation inventory systems.

🍯 That’s why we are building Syrup, an AI-powered predictive software platform for inventory decisions in commerce. Our team of data scientists develops cutting-edge forecasting methodologies to deliver market-leading precision and accuracy. Merchandising and planning teams benefit from buying, allocation, and inventory balancing workflows that increase confidence and improve financial outcomes.

🚀 Our mission is to create a world where enterprises make the best use of their scarce physical resources and time, strengthened by infinite intelligence at every step in the value chain.

👔 We're backed by leading investors, including Accel and Google's AI fund (Gradient Ventures). Our customers range from industry legends to promising upstarts, including Gap, Abercrombie & Fitch, Salomon, Faherty, and Reformation, among others.

About The Role

As a Senior Full Stack Data Scientist, you will be an integral part of our core team, driving the development of our groundbreaking demand forecasting engine for apparel. This role offers a unique opportunity to contribute to a predominantly greenfield project in a fast-growing, machine-learning startup. You will collaborate closely with a dynamic and diverse team of data scientists, software engineers, business experts, and visionaries.

In this critical function, you will play a key role in revolutionizing how inventory decisions are made for apparel brands and retailers. Join us on our mission to empower 100x better decision-making through the creation of intuitive and predictive software!

You Will
  • Lead the development of forecasting algorithms that power decision-making systems moving millions of dollars of inventory around the world.

  • Collaborate on a predominantly greenfield project, leveraging your expertise to drive innovation and deliver value.

  • Partner with product managers, other data scientists, and engineers to identify new opportunities for incorporating 1st-party customer behavior signals and 2nd-party data to further enhance forecast accuracy.

  • Contribute to a fast-growing startup, where your ideas and contributions will have a direct and meaningful impact.

  • Be part of a dynamic and diverse team that values collaboration, creativity, and pushing the boundaries of what's possible.

  • Play a pivotal role in building intuitive and predictive software that will redefine decision-making processes in the industry.

You Have
  • Proven experience in a fast-paced startup environment, successfully building new systems from prototype to production.

  • Collaborative mindset, able to work with customers, partners, Customer Success, Product, Engineering, and Analytics teams.

  • Demonstrated pragmatic technical judgment in selecting machine learning algorithms and adapting them to solve real world problems. (Bonus: a focus on time series problems or demand forecasting)

  • Ability to start small and incrementally extend the data science platform while improving scalability and performance.

  • Proven commitment to operational excellence, ensuring the smooth operation of an always-on, always-shipping SAAS product.

  • 4+ years of experience as a Data Scientist

Deep technical expertise in:
  • At least two mainstream machine learning libraries or frameworks like PyTorch, Tensorflow, scikit-learn, and XGBoost.

  • Handling data of all shapes and sizes. A dataset’s size or format doesn’t stop you from being able to build quick POC’s or robust pipelines.

  • Scaling and monitoring complex machine learning pipelines that involve dozens of models and millions of business-critical predictions each week.

  • Experience in optimizing data models and access patterns for modern warehouse and orchestration platforms such as Snowflake, Redshift, Databricks, Spark, DBT, Apache Airflow, and Prefect.

  • Proficiency in Python, Pandas, and working with columnar formats like parquet.

  • Significant mathematics background including statistics and probability.

What We Offer

Fun, friendly, respectful, collaborative, diverse, driven, mission-oriented — that’s Syrup! We're a group of driven people who want to make a difference in the world by building game-changing software. We care deeply about people, planet, and product. Concretely, we offer:

  • Remote Flex: We’re a remote first team across Europe and North America. For our colleagues in New York, you can come into our office in SoHo as often as you like.

  • Equity Compensation: We offer generous equity compensation for all our early employees.

  • Health, Dental, Vision: We offer generous health, vision, and dental benefits to our employees.

  • Generous PTO: Take all the time you need, whenever you need it.

  • Syrup Summits: We bring teams together every quarter for our Syrup summits. Previous locations: Barcelona, Tuscany, Madrid, Los Angeles, Nashville, Boston, New York.

We offer competitive base pay with salary of $130,000 - $180,000 based on location and commensurate with experience, generous early-stage equity package, and benefits including medical / dental / vision.

Top Skills

Apache Airflow
Databricks
Dbt
Pandas
Prefect
Python
PyTorch
Redshift
Scikit-Learn
Snowflake
Spark
TensorFlow
Xgboost
Am I A Good Fit?
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The Company
HQ: New York, New York
53 Employees
Year Founded: 2020

What We Do

Syrup helps you plan, allocate, and buy with confidence. Use pinpoint-accurate demand signals and intelligent optimization recommendations, all powered by AI, to increase margins while growing your apparel or footwear brand.

Backed by leading investors including Accel and Gradient Ventures.

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