Data Scientist

Data Scientist ScandyCandy LLC Miami, FL Job Details Full-time $85,347.88 - $102,784.55 a year 15 hours ago Benefits Paid time off Qualifications AI models Systems integration Data visualization software proficiency Sales analytics & reporting tools Software coding NumPy AI platforms (beyond public GPTs) Computational framework Digital marketing tools SQL Pandas Production systems Machine learning cloud services Business intelligence tools Machine intelligence Bachelor's degree Model deployment Integration Platforms (Enterprise solutions) Data-driven problem-solving Machine learning frameworks Data analysis software Database software proficiency

Full Job Description ScandyCandy LLCLocation:

Miami, Florida (Remote) About the Job ScandyCandy is a rapidly expanding omnichannel retail and eCommerce company specializing in Scandinavian confectionery products across the United States. The company currently operates multiple retail locations, and is executing an aggressive national growth strategy, including expansion into Sarasota, Boca Raton, Aventura Mall, and the Chicago market. To support this expansion, ScandyCandy seeks its first Data Scientist responsible for designing and managing the company's enterprise data platforms, AI initiatives, predictive analytics capabilities, and cloud based business intelligence systems. The Data Scientist will leverage structured and unstructured data across retail operations, eCommerce platforms, marketing systems, and internal applications to improve business decision-making and automate operational workflows. The role reports directly to the CEO of ScandyCandy. The position requires advanced knowledge of data science, cloud computing, machine learning, software integration, and statistical modeling to support a high-growth, multi-location retail organization. ResponsibilitiesEnterprise Data Platform Design, build, and maintain centralized data architecture integrating Shopify, Square, Klaviyo, Supabase, and internal business applications. Develop and manage ETL and ELT pipelines using API integrations to collect, transform, and normalize operational data. Data Exploration, Cleaning, and Validation - Perform in-depth data exploration, quality assessment, cleaning, governance, and feature engineering to ensure reliable inputs for modeling and analysis Create scalable cloud-based data models to support future expansion from multiple retail locations to a national footprint. Machine Learning and Artificial Intelligence Develop and deploy machine learning models using Databricks to forecast customer demand, inventory requirements, and sales trends. Design predictive analytics models to optimize product assortment, customer retention, and purchasing behavior. Experience using generative AI tools (LLMs, Claude, AI coding assistants) as part of a professional analytics workflow—not just experimentation. Implement AI-powered recommendation engines and personalization models for digital commerce platforms. Develop AI automation solutions including customer support chatbots and intelligent email response systems. Retail and eCommerce Analytics Analyze customer behavior across physical stores and online channels. Build executive dashboards measuring revenue, customer acquisition, customer lifetime value, inventory turnover, and marketing performance. Monitor sales trends across geographic markets to support future retail expansion decisions. Marketing and Customer Intelligence Analyze digital marketing performance across TikTok, Instagram, email marketing campaigns, and eCommerce channels. Direct involvement in experimentation or A/B testing, including hypothesis definition, measurement, and interpretation Develop customer segmentation models and targeted marketing strategies. Measure campaign attribution and return on advertising investment. Cloud Infrastructure and Data Governance Maintain secure and scalable cloud data infrastructure. Manage API connectivity between Square, Shopify, Slack, Klaviyo, Supabase, and enterprise analytics platforms. Develop data governance policies, quality controls, and reporting standards. Business Strategy and Expansion Provide analytical support for new store site selection and expansion planning. Develop forecasting models supporting the company's growth from existing operations into new regional markets. Collaborate with executive leadership to develop long-term AI and digital transformation strategies. Required Qualifications Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Information Systems, Mathematics, Artificial Intelligence, Machine Learning, or a closely related field. 5+ years of experience in data science, advanced analytics, or related roles delivering production-grade data solutions Advanced knowledge of Python and SQL (pandas, NumPy, scikit-learn, XGBoost, etc.) Proven track record of deploying machine learning frameworks and statistical modeling. Experience working with cloud data platforms and enterprise databases. Experience integrating multiple API driven business systems. Experience with cloud platforms (AWS, Azure, or GCP) for data and ML workloads Experience with data visualization / BI tools (Tableau, Power BI, or similar) Hands-on experience with Databricks or similar machine learning platforms. Strong analytical and problem-solving abilities. Preferred Technical Skills Proficiency in Python, SQL, Java or Spark for statistical modeling and data wrangling. Solid grasp of Databricks to build Machine Learning Prediction Models AI/LLM tools applied to analysis, workflow efficiency, or knowledge management. Familiarity with Shopify APIs, Square APIs, Slack APIs, Supabase, PostgresSQL and cloud data warehousing. Technical Proficiency with big data tools like Spark and Kafka. Strong analytical, problem-solving, and critical thinking skills. Experience building dashboards and business intelligence solutions using Amazon QuickSight (or similar tools such as Tableau, Power BI). Familiarity with digital analytics tools (e.g., Google Analytics, Adobe Analytics). Understanding of ETL/ELT design and customer segmentation pipelines. QSR, retail, ecommerce, or other high-volume transactional environments. AI/LLM tools applied to analysis, workflow efficiency, or knowledge management. Effective communication, both orally and in writing. Ability to work independently and collaboratively in a fast-paced, dynamic environment, demonstrating strong organization, prioritization, and follow-through. What we offer Executive-level visibility with a direct impact on core business metrics. Opportunity to work on high-impact analytics projects that shape ecommerce strategy. Remote work model, there may still be occasions when you are required to work in person at our Miami office. Collaborative culture with cross-functional team integration. A fast-paced, high-growth environment with significant learning opportunities Competitive Bonus and Equity programs. Work Hours Employees are expected to work a minimum of forty (40) hours per week and such additional hours as reasonably necessary to fulfill workplace responsibilities and ensure successful operations. Paid Time Off Employees shall be entitled to fifteen (15) days of paid time off ("PTO") per year. Sick Time - All full-time employees receive 80 hours of sick time each year.

The base salary range:

$74,996 - $100,000 Pay ranges are a general guideline and not intended as a guaranteed and/or implied final compensation or salary for this job opening. Determination of official compensation or salary relies on several different factors including, but not limited to: level of position, complexity of job responsibilities, geographic location, work experience, education, certifications, Federal Government contract labor categories, and contract wage rates. The Data Scientist position is critical to ScandyCandy's strategic expansion initiatives and digital transformation efforts. As the company expands into multiple new markets and continues to grow its eCommerce presence, advanced data science capabilities are necessary to integrate business systems, optimize inventory management, automate customer engagement, improve marketing performance, and support executive decision-making through predictive analytics and artificial intelligence.

Pay:

$85,347.88 - $102,784.55 per year

Work Location:

In person