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Why careerforge?
careerforge is a global retail and technology powerhouse that is redefining the way millions of customers shop, save, and experience everyday life. With a presence in more than 20 countries and a digital ecosystem that spans e‑commerce, mobile, in‑store, and supply‑chain platforms, careerforge offers a unique blend of scale, innovation, and impact. Our mission—“helping people save money so they can live better”—drives every decision, from responsible sourcing to cutting‑edge sustainability initiatives. As a member of the careerforge family, you will be part of a forward‑thinking organization that values curiosity, collaboration, and continuous learning.
About the Data Services Team
The Data Services team operates like a high‑velocity startup incubated inside careerforge. Partnering closely with US stores, e‑commerce divisions, and cross‑functional business units, we deliver a suite of data products that turn raw information into actionable, customer‑centric insights. Our focus areas include customer experience, store operations, supply‑chain optimization, and personalized marketing. By leveraging modern data engineering, advanced analytics, and machine learning, we empower merchants, suppliers, and internal stakeholders to make smarter, faster decisions across the omnichannel landscape.
Key Responsibilities
As a Staff Data Scientist and technical lead for all data‑technology initiatives, you will own end‑to‑end delivery of high‑impact analytics solutions. Your day‑to‑day responsibilities include:
- Data Source Identification & Acquisition: Define business‑critical data requirements, evaluate internal and external data assets, and conduct initial data quality assessments.
- Problem Formulation & Business Impact: Translate ambiguous business challenges into clear analytical problems, set measurable objectives, and quantify expected ROI.
- Analytical Modeling & Feature Engineering: Design and iterate on models that handle massive, multi‑structured datasets, employing statistical analysis, hypothesis testing, and experimental design.
- Advanced Machine Learning Development: Build state‑of‑the‑art solutions using deep learning, reinforcement learning, and large‑language models, while staying abreast of emerging AI research.
- Model Deployment & Scaling (MLOps): Collaborate with MLOps engineers to containerize, monitor, and continuously improve models in production, ensuring robustness and scalability.
- Code Development & Testing: Write production‑grade Python or R code, develop unit and integration tests, produce proof‑of‑concepts, and maintain comprehensive documentation.
- Business Acumen & Stakeholder Influence: Partner with product owners, senior leadership, and external partners to align analytics initiatives with strategic goals and secure funding.
- Model Validation & Governance: Define validation metrics, conduct rigorous testing for accuracy, fairness, and reliability, and maintain audit trails for compliance.
- Data Visualization & Storytelling: Craft compelling visual narratives using tools such as Tableau, Power BI, or custom D3.js dashboards, translating complex findings into clear business recommendations.
- Mentorship & Team Leadership: Review junior team members’ deliverables, provide technical guidance, and champion best practices across the data science community.
Essential Qualifications
To thrive in this role, you should possess the following core credentials:
- Education: Bachelor’s degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field (Master’s or Ph.D. preferred).
- Experience: Minimum 4 years of hands‑on experience in data science, analytics, or machine learning within a fast‑paced, data‑driven environment.
- Technical Proficiency: Expert‑level programming skills in Python and/or R, with a strong command of libraries such as pandas, scikit‑learn, TensorFlow, PyTorch, and Spark.
- Machine Learning Expertise: Deep understanding of supervised, unsupervised, and reinforcement learning algorithms, as well as experience with large‑scale model training and deployment.
- Data Engineering Foundations: Ability to design robust data pipelines, work with relational and NoSQL databases, and leverage cloud platforms (AWS, GCP, Azure).
- Communication Skills: Proven ability to convey technical concepts to non‑technical audiences, influence senior stakeholders, and produce clear documentation.
- Leadership Capability: Demonstrated experience leading projects end‑to‑end, mentoring junior analysts, and establishing best‑practice standards.
Preferred Qualifications & Additional Strengths
- Advanced degree (M.S. or Ph.D.) in a quantitative discipline.
- Hands‑on experience with MLOps tools such as Kubeflow, MLflow, or Seldon.
- Familiarity with streaming data frameworks (Kafka, Flink) and real‑time analytics.
- Track record of delivering production‑grade AI solutions that generated measurable business value.
- Experience in retail, e‑commerce, or supply‑chain analytics.
- Proficiency in data visualization platforms (Tableau, Power BI, Looker) and storytelling techniques.
- Knowledge of privacy regulations (GDPR, CCPA) and ethical AI principles.
Core Skills & Competencies
- Analytical Thinking: Ability to dissect complex problems, formulate hypotheses, and design experiments that drive insight.
- Strategic Vision: Align data initiatives with broader business objectives and anticipate future analytical needs.
- Collaboration: Work seamlessly across product, engineering, and business teams, fostering a culture of shared ownership.
- Adaptability: Thrive in a dynamic environment where priorities shift rapidly and new data sources emerge.
- Quality‑First Mindset: Champion code quality, reproducibility, and rigorous testing throughout the model lifecycle.
- Continuous Learning: Stay current with the latest AI research, tools, and industry trends, and disseminate knowledge within the team.
Career Growth & Learning Opportunities
careerforge invests heavily in the professional development of its talent. As a Staff Data Scientist, you will have access to:
- Mentorship from senior leaders in AI and analytics.
- Sponsored certifications (e.g., AWS Certified Machine Learning, TensorFlow Developer).
- Internal hackathons, data‑science bootcamps, and research collaborations with leading universities.
- Clear promotion pathways to Principal Scientist, Director of Data Science, or AI Strategy roles.
- Opportunities to publish research, present at industry conferences, and contribute to open‑source projects.
Work Environment & Culture at careerforge
Our remote‑first policy empowers you to work from anywhere in the United States while staying tightly connected to a vibrant, inclusive community. careerforge champions:
- Diversity & Inclusion: A workforce that reflects the customers we serve, with employee resource groups and inclusive hiring practices.
- Innovation Mindset: A “startup‑in‑a‑corporation” culture that encourages experimentation, rapid prototyping, and data‑driven decision‑making.
- Work‑Life Balance: Flexible schedules, generous paid time off, and a focus on mental‑health resources.
- Collaboration Tools: State‑of‑the‑art communication platforms (Slack, Teams, Miro) and virtual coworking spaces to keep teams aligned.
Compensation, Perks & Benefits
careerforge offers a competitive hourly rate of $30‑$40 per hour, complemented by a comprehensive benefits package that includes:
- Medical, dental, and vision coverage for you and your dependents.
- Retirement savings plans (401 k) with company match, stock purchase options, and life insurance.
- Generous employee discounts both online and in‑store.
- Education assistance for you and eligible family members.
- Parental leave, paid sick leave, and short‑ and long‑term disability coverage.
- Wellness programs, including virtual fitness classes and mental‑health resources.
- Opportunities for career mobility across careerforge’s global network of business units.
How to Apply
If you are passionate about turning massive data sets into strategic advantage, love mentoring the next generation of data scientists, and thrive in a remote, high‑impact environment, we want to hear from you. Join careerforge and help shape the future of retail, technology, and customer experience.
Apply Now – Start Your Journey with careerforge!
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