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Principal Applied Scientist - Remote USA (*eligible states) image - Rise Careers
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Principal Applied Scientist - Remote USA (*eligible states)

About The RoleThe RealReal is the world’s largest authenticated luxury resale marketplace. We partner with our 34M+ buyers and consignors to build a more sustainable future for fashion, and that starts with our employees. If you want to be a part of building a more sustainable world, and are passionate about applying your machine learning and AI skills to delight our customers, we’d love for you to join our dynamic team!The Principal Applied Scientist will be pivotal in advancing the Pricing team’s objectives by leading key applied science projects that address complex business challenges from initial list price, discounting, and promotions. This role involves close collaboration with Product and Engineering partners to develop technical roadmaps and deliver Machine Learning solutions that drive impactful OKR’s, such as improving model performance, enhancing pricing-related revenue generation and optimizing the efficiency of model deployment pipelines.• States Not Eligible: AK, AR, DE, KS, MS, ND, SD, WYWhat You Get To Do Every Day• Considered a subject-matter expert (SME) in one or two domains, such as econometrics, algorithmic pricing and bidding, marketing science, and causal inference models.• Partner closely with cross-functional teams to ensure alignment of ML solutions with broader business goals.• Lead the design, development and deployment of Machine Learning models that solve key/strategic business problems, focusing on scalability, reliability, and performance.• Develop and maintain clean, efficient, and scalable code that meets industry standards. Ensure code is well-documented and easily accessible for future iterations and optimizations, fostering best practices in coding and model deployment.• Conduct deep analyses on complex datasets to derive actionable insights, employing state-of-the-art methodologies such as deep learning frameworks (e.g., TensorFlow, PyTorch), counterfactual reasoning, and causal inference.• Utilize cutting-edge ML methodologies and frameworks to develop robust, scalable models that solve high-impact pricing and discounting problems, enhancing our ability to predict and optimize product pricing with a high degree of accuracy.• Influence technical direction and take ownership of key components within the pricing and discounting ecosystems, ensuring solutions are built to support current and future business needs.• Collaborate with key stakeholders in the development of data-driven solutions and deployable products. Contribute to the development of technical roadmaps and product initiatives.• Provide mentorship to junior and mid-level ML engineers, fostering team expertise in pricing-related ML domains.• Contribute to the company’s intellectual property and technical leadership through patents and publications at top-tier conferences and journals.What You Bring To The RoleMinimum Requirements:• 10+ years of industry experience in applied Machine Learning, including a proven track record in designing, deploying, and scaling production-level ML models• Master’s or PhD in AI, Computer Science, Econometrics, Mathematics, Statistics, Electrical Engineering or related field• 8+ years experience in building, deploying, and managing machine learning models in production environments at scale, with a focus on pricing, discounting, algorithmic bidding, or similar complex domains• Extensive knowledge of ML best practices (A/B testing, experiment design, training/serving pipelines, feature engineering) and advanced ML algorithms/techniques (gradient boosting, deep neural networks, optimization, regularization)• Experience in at least one of these domains: price optimization, discounting, algorithmic bidding• Extensive experience in scientific and ML libraries in Python (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (Tensorflow, Keras, PyTorch)• Strong data engineering skills and experience working with large scale datasets, including data preprocessing, feature extraction, and efficient data handling• Hands-on experience with big data tools (Apache Beam, Apache Kafka, Spark) for distributed processing of large datasets.• Proficiency with cloud platforms (AWS, GCP, or Azure) for scalable model deployment and data storage solutions• Fluency in Python and SQL for data manipulation, querying, and analysisPreferred Requirements:• PhD in Computer Science, Machine Learning, Econometrics, AI or related field• Strong background in applying Machine Learning techniques to solve real-world business problems in the retail or e-commerce sector• Hands-on experience with MLOps tools and pipelines, enabling smooth model lifecycle management• Impact-focused mindset, with a commitment to delivering high-quality, business-oriented ML solutions• Demonstrated leadership and mentoring skills, with experience leading and inspiring technical teamsCompensation, Benefits, + Perks• Employee Stock Purchase Plan• 401K with Company Match• Medical, Dental & Vision Insurance• Paid Parental Leave• Unlimited Discretionary Time Off (DTO)* and 10 Paid Company Holidays• * Unlimited DTO with Manager approvalThe expected salary range for this role is $249,734.00-$277,482.00. To determine starting pay we carefully consider a variety of factors, including primary work location and an evaluation of a candidate’s skills, experience, market demands, and internal parity. Additionally, salary is just one component of TRR’s total rewards package. Depending on role, employees may also be eligible for a bonus program, incentive pay and benefits.The RealReal is the world’s largest online marketplace for authenticated, resale luxury goods, with more than 30 million members. With a rigorous authentication process overseen by experts, The RealReal provides a safe and reliable platform for consumers to buy and sell their luxury items. We have hundreds of in-house gemologists, horologists and brand authenticators who inspect thousands of items each day. As a sustainable company, we give new life to pieces by thousands of brands across numerous categories—including women's and men's fashion, fine jewelry and watches, art and home—in support of the circular economy. We make selling effortless with free virtual appointments, in-home pickup, drop-off and direct shipping. We do all of the work for consignors, including authenticating, using AI and machine learning to determine optimal pricing, photographing and listing their items, as well as handling shipping and customer service. At our 13 retail locations, including our twelve shoppable stores, customers can sell, meet with our experts and receive free valuations.The RealReal is committed to providing an equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or expression, or Veteran status. We will consider qualified applicants for a position regardless of arrest or conviction records. At TRR, People Come First. That’s why diversity and inclusion are vital to our priorities as an equal opportunity employer. You can read about our Diversity Equity and Inclusion program here.Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. The employee is regularly required to sit; use hands to finger, handle, or feel and talk or hear. The employee is occasionally required to stand; walk; reach with hands and arms; climb or balance; stoop, kneel, crouch, or crawl; and taste or smell. The employee must occasionally lift and/or move up to 10 pounds. Specific vision abilities required by this job include close vision. The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job.
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CEO of The RealReal
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John Koryl
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Authenticity We stand by the authenticity of our products and strive for authenticity in everything we do. Respect We respect the heritage of the brands we sell, the trust we have with our consignors and customers, and the commitment of our empl...

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Full-time, remote
DATE POSTED
November 29, 2024

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