Postdoctoral In Bayesian Statistics Jobs in New York

This role is not eligible for employer sponsored visas. Applicants must be legally authorized to work in the United States without the need for company sponsorship now or in the future.

Jr. Data Scientist
Location: Brooklyn, NY (4 days On-site / 1 day WFH)

About Us:

At Focus Camera, we fuel creativity, support our partners, and deliver exceptional customer experience. Guided by our core values—teamwork, responsibility, excellence, adaptability, and results—we collaborate to build scalable solutions that drive growth.

Founded in 1966 as a family-owned business, Focus Camera has grown to 150+ employees across three locations: our Brooklyn headquarters and store, our 90,000 sq. ft. warehouse in North Brunswick, NJ, and our Lakewood, NJ retail store. We specialize in consumer electronics and pro audio, partnering with leading brands such as Sony, Nikon, Fujifilm, Yamaha, Fender, and Ninja selling thousands of products across several online platforms such as Amazon, Best Buy, and Walmart.

Role Overview:

The Data Science Team supports the company’s ecommerce platforms and adjacent teams by managing advertising campaigns and ensuring high quality reporting processes. This role will assist other departments with as-needed KPI reporting- sales, advertising expenditure, etc. The initial focus will be accurate reporting and understanding of internal data processes. Eventually, the role will help to maintain reporting pipelines and dashboards and expand on these further.

The role will need to communicate analyses results/reports to other departments and executives regularly.

Responsibilities:

• Extract, transform, and analyze data from advertising platforms (e.g., Google Ads, Amazon Ads) and internal databases using SQL and Python to identify trends, anomalies, and optimization opportunities.
• Design, build, and maintain production-grade ETL pipelines using SQL and Python; improve reliability, scalability, and data quality.
• Own the end-to-end development of machine learning models, including problem formulation, feature engineering, training, evaluation, deployment, and iteration.
• Develop and experiment with advanced modeling techniques, including reinforcement learning, regression, and other statistical/ML approaches to improve marketing and sales outcomes.
• Maintain and enhance internal dashboards and reporting tools used to track advertising and business performance (e.g., Power BI).
• Perform ad-hoc analysis to support strategic decisions across marketing, growth, and operations.

Requirements:

• 2+ years of experience using Python for data ingestion, analysis, and machine learning (R acceptable background, but Python is required for this role)
• 2+ years of experience using SQL for data analysis and data pipeline development
• MySQL and/or Microsoft SQL Server preferred
• 1+ years of hands-on data engineering experience, including building and maintaining ETL pipelines
• Proven experience owning and building machine learning models from scratch (not just tuning or consuming existing models)
• 1+ years of experience with cloud platforms such as AWS and/or Azure
• Experience working with version control systems (Git/GitHub) in a collaborative environment
• Strong understanding of data modeling, validation, and analytics best practices

Nice-to-have:

• Experience with reinforcement learning or experimentation-driven ML systems
• Hands-on experience with Google Ads, Amazon Ads, or other eCommerce advertising platforms
• Familiarity with SEO analytics and organic search performance measurement
• Experience with Power BI or similar dashboarding/BI tools
• Experience working with large-scale marketing or eCommerce datasets
• Background in Bayesian statistics, regression analysis, or causal inference

Exposure to GCP in addition to AWS/Azure

• Collaborate closely with cross-functional partners (marketing, product, engineering) to understand requirements and deliver actionable insights.
• Contribute to process improvements, data architecture decisions, and best practices for analytics, ML, and data engineering workflows.
• Support and help implement new data-driven strategies to achieve sales and marketing goals.