Lead Data Scientist, Search (REMOTE)

DICK'S Sporting Goods

1d•$95,200 - $158,800•Remote

About The Position

Are you a passionate technologist with experience in AI, Machine Learning, Data Science and Analysis? Are you looking for an opportunity to drive enterprise impact and shape the future of a leading sports retailer with $12B+ in revenue and 800+ physical stores? Do you enjoy working with a highly skilled team of Machine Learning engineers & Scientists, co-creating enterprise grade AI capabilities? As the Lead Data Scientist, Search, you will be a key technical leader in our athlete and teammate transformation that aims to deliver a best in class customer and teammate search experience by providing them advanced intelligent decisioning tools using AI/GenAI and Machine Learning at its core. This is an exceptional opportunity to transform the way we deliver omnichannel search by building foundational AI/GenAI capabilities and do career defining work in the space. Job Purpose: This role will require an emerging technical leader & subject matter expert with strong experience in traditional Machine Learning algorithms along with deep understanding of the cutting edge SOTA AI/GenAI methods used in search engines. As a technical leader you will be influencing critical enterprise technical strategies both in the Machine Learning/AI space and neighboring integration spaces like frontend, search engineering, DSP, backend data systems etc. You will partner with product, business, and engineering leads to design search systems for future growth and scale and help them understand the art of the possible on search experiences with AI technology through deep technical design.

Requirements

6+ years of experience in the field with at least 2-3 years of being the main technical lead in related projects (strongly preferred)
Experience in varied search systems, like Elastic, SOLR, with deep understanding of their underlying infrastructure and customization capabilities.
Experience being the technical lead of multiple projects at the same time, responsible for delivery and business metrics
Experience in API engineering, including designing, developing and maintaining APIs
Extensive experience using common machine learning and deep learning frameworks such as TensorFlow, PyTorch, OpenAI, and LangChain
Expert understanding of Python and other common languages.
Expert level experience in big data technologies including but not limited to Spark, Kafka, distributed systems computing etc.
Experience in an Agile working environment and at least one related project management tool (Azure DevOps, Jira, etc.)
Previous experience mentoring, training, and developing junior members of the team through technical influence.
Experience with software engineering principles as it relates to Machine Learning systems.
Comfortable presenting results to and influencing senior and executive leadership on strategic technical decisions, from the lens of science.
Deep understanding of SOTA machine learning models in the overall search space.
Brings a collaborative, problem solving and growth mindset to all interactions with a strong focus on delivery.

Nice To Haves

Bonus if specific experience in cutting edge multi-modal systems.

Responsibilities

Lead design and implementation of advanced algorithms that improve multi-modal search performance, including using embeddings, graph learning, deep learning and large language models (LLMs), by refining query understanding, retrieval, ranking and whole page optimization.
Developing & Optimizing Ranking Algorithms: Designing and deploying ranking algorithms that go beyond keyword matching to consider content quality, user experience and various site-level factors for determining the order of search results.
Search Personalization: Develop & Implement AI/ML driven search personalization algorithms that learn from user behavior & preferences to deliver tailored search results based on user metadata like location, past site behavior etc.
Expertise in data systems: Collaborate with data & search engineers to build robust data pipelines for collecting, transforming & managing massive datasets required for efficient operation of search systems. This includes unique challenges of integrating & synchronizing multimodal data streams.
Search Architecture Design & Optimization: Collaborating with software engineers and architects to design and optimize the underlying infrastructure supporting the search engine.
Performance Monitoring & Optimization: Developing and implementing tools & processes to monitor the performance of search systems in real time, detecting anomalies, ensuring data quality, and addressing technical issues to maintain the efficiency & effectivenss of the search system.
Experimentation & A/B testing: Collaborate with analytics teams to design, conduct and analyze controlled experiments that evaluate search performance, bringing in deeper insights that help validate hypotheses about impact of search algorithms.
Research & development of emerging technologies: Staying updated with the latest advancements in AI, ML & search technologies and exploring opportunities to incorporate these innovations into search systems.
Mentor junior scientists and machine learning engineers in their technical work and help establish a deep technical community invested in search experiences improvement.
Work collaboratively across functions to drive scalable, robust technical solutions and be part of the engineering technical leader community.