- Страна
- США
- Зарплата
- 97 000 $ – 166 750 $
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Senior Data Scientist (P4528)
Отличное предложение от стабильной компании с доступом к уникальным данным. Хороший социальный пакет и прозрачная вилка зарплаты, однако требование 5-дневной офисной работы может подойти не всем.
Сложность вакансии
Роль требует сочетания навыков классического ML, оптимизации и серьезной программной инженерии (написание пакетов, MLOps). Высокая планка по качеству кода и обязательное присутствие в офисе 5 дней в неделю повышают порог входа.
Анализ зарплаты
Указанный диапазон ($97k – $167k) полностью соответствует рыночным стандартам для Senior MLE в таких городах, как Цинциннати и Чикаго. Медиана рынка для этой роли в США составляет около $150k-160k.
Сопроводительное письмо
I am writing to express my interest in the Senior Machine Learning Engineer position within the SCORe team at 84.51°. With a strong background in developing enterprise-scale ML models and a deep proficiency in Python, I am particularly drawn to this role's focus on contributing to multi-contributor packages and scaling optimization sciences. My experience in data wrangling and implementing MLOps practices aligns perfectly with your need for robust, well-tested code that supports near real-time science delivery.
Throughout my career, I have focused on creating computationally efficient solutions and maintaining high coding standards. I am excited about the opportunity to leverage Kroger's extensive first-party data to drive customer-centric journeys and improve supply chain efficiency. I look forward to the possibility of bringing my technical expertise and collaborative mindset to your Cincinnati-based team.
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Описание вакансии
84.51° Overview:
84.51° is a retail data science, insights and media company. We help The Kroger Co., consumer packaged goods companies, agencies, publishers and affiliates create more personalized and valuable experiences for shoppers across the path to purchase.
Powered by cutting-edge science, we utilize first-party retail data from more than 62 million U.S. households sourced through the Kroger Plus loyalty card program to fuel a more customer-centric journey using 84.51° Insights, 84.51° Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.
84.51° follows a 5‑day in‑office work schedule to support collaboration, alignment, and team connection.
Join us at 84.51°!
________________________________________________________
Senior Machine Learning Engineer (P4528)
Summary
The Supply Chain, Operations, and Replenishment (SCORe) team is seeking a Senior Machine Learning Engineer (MLE)to support supply chain workstreams, focusing on contributing robust, well-tested code to a multi-contributor package that supports optimization sciences. This role combines foundational software development capabilities, applied ML and optimization research, and package design to scale to the enterprise. You will contribute code daily and collaborate with cross-functional partners to define, deliver, and scale supply chain optimization sciences.
Responsibilities
- Lead the development and delivery of analytical plans to support client roadmaps, ensuring the adoption of best practices and innovative ideas.
- Scope and manage work from inception to completion, ensuring timely delivery to specifications.
- Develop and support MLOPs for production sciences.
- Collaborate with stakeholders to understand client objectives and customer insights, designing best-in-class solutions.
- Partner with engineering, product, and research teams to implement best practices for analysis, storage, and quality assurance.
- Implement software solutions using best practices of coding standards and quality assurance with regards to maintainability and testing.
- Identify opportunities for standardization and automation of existing solutions/processes, contributing to enhancements that maximize team potential and stakeholder value.
- Interpret business results and develop actionable recommendations from data analysis to build relevant customer stories for stakeholders.
- Challenge and improve 84.51° analytic capabilities, solutions, and best practices.
- Follow best practices in space/resource management to ensure efficient utilization of analytic resources and timely delivery of business deliverables.
- Partner with leaders across projects to prioritize work, identify risks and opportunities, and streamline team execution.
- Support the near real-time science delivery of optimization models.
Qualifications, Skills, and Experience
- Bachelor's degree in mathematics, statistics, analytics, data science, or a related discipline.
- 2+ years of experience using advanced algorithms, programming languages, or technologies to develop technical analytics solutions or capabilities.
- 2+ years experience developing and implementing enterprise-scale machine learning and/or optimization models.
- Proficiency in querying data from relational databases.
- Experience using Python, or similar statistical software to develop analytical solutions.
- Expertise in data wrangling, data cleaning and preparation, and dimensionality reduction.
- Ability to create computationally efficient solutions.
- Strong analytical, creative problem-solving, and decision-making skills.
- Strong business acumen; grocery and/or supply chain experience is a plus.
- Passionate about data, analysis, and insights.
- Natural curiosity that embraces change and a willingness to try new things and learn from failure.
- Ability to work in a highly collaborative environment.
#LI-SSS
Pay Transparency and Benefits
- The stated salary range represents the entire span applicable across all geographic markets from lowest to highest. Actual salary offers will be determined by multiple factors including but not limited to geographic location, relevant experience, knowledge, skills, other job-related qualifications, and alignment with market data and cost of labor. In addition to salary, this position is also eligible for variable compensation.
- Below is a list of some of the benefits we offer our associates:
- Health: Medical: with competitive plan designs and support for self-care, wellness and mental health. Dental: with in-network and out-of-network benefit. Vision: with in-network and out-of-network benefit.
- Wealth: 401(k) with Roth option and matching contribution. Health Savings Account with matching contribution (requires participation in qualifying medical plan). AD&D and supplemental insurance options to help ensure additional protection for you.
- Happiness: Paid time off with flexibility to meet your life needs, including 5 weeks of vacation time, 7 health and wellness days, 3 floating holidays, as well as 6 company-paid holidays per year. Paid leave for maternity, paternity and family care instances.
Pay Range
$97,000—$166,750 USD
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Навыки
- Python
- Machine Learning
- MLOps
- SQL
- Optimization
- Data Wrangling
- Software Development
- Statistics
Возможные вопросы на собеседовании
Позиция предполагает работу над общим пакетом кода для оптимизации. Важно понимать, как кандидат обеспечивает качество в командной разработке.
Расскажите о вашем опыте разработки переиспользуемых Python-пакетов. Как вы организуете тестирование и контроль версий в многопользовательской среде?
Команда занимается оптимизацией цепочек поставок (SCORe). Важно выявить опыт в этой специфической области.
Какие методы оптимизации или алгоритмы машинного обучения вы бы применили для решения задачи прогнозирования спроса или пополнения запасов в ритейле?
Вакансия требует навыков MLOps для производственных систем.
Опишите ваш опыт внедрения MLOps. Как вы обеспечиваете мониторинг моделей и их обновление в режиме реального времени?
Работа с данными 62 миллионов домохозяйств требует навыков написания эффективного кода.
Как вы подходите к оптимизации производительности Python-кода при обработке больших объемов данных? Приведите пример из практики.
Роль Senior предполагает взаимодействие с бизнесом и перевод их нужд в технические решения.
Как вы транслируете сложные результаты аналитических моделей в понятные бизнес-рекомендации для стейкхолдеров?
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- Страна
- США
- Зарплата
- 97 000 $ – 166 750 $