Data Analyst

We are hiring a Senior Data Analyst / Analytics Lead for our client - a fast-growing consumer health brand in the gut health / probiotics space, primarily operating in the U.S. market.
The company sells its products through major retail chains and leading online marketplaces and is rapidly scaling its e-commerce and retail operations.

We are looking for a data-driven and business-oriented Senior Data Analyst / Analytics Lead who will help turn complex data into actionable insights and support strategic decision-making across the company’s omnichannel business, including Amazon, TikTok Shop, Shopify, Walmart, and Target.
In this role, you will work closely with Marketing, eCommerce, and Finance teams to understand business performance, identify growth opportunities, improve profitability, provide senior leadership with clear, data-backed recommendations, and build scalable analytical systems using modern AI-powered tools.

WHAT YOU WILL DO
Analyze marketplace, retail, and DTC performance to identify key drivers of growth, decline, and profitability
Analyze Shopify growth and customer acquisition performance driven by Meta Ads, and partner with the Marketing team to connect Meta Ads performance with Shopify sales and customer data to identify campaigns and acquisition strategies that drive sustainable, profitable growth
Conduct in-depth analysis of TikTok Shop performance, including key growth, conversion, and profitability drivers
Analyze performance across key e-commerce and retail channels
Support retail and marketplace performance tracking, planning, and forecasting
Build and maintain dashboards, reports, and analytical models to support business decision-making
Build and improve analytical systems and workflows using AI tools, reducing manual work and accelerating insight generation
Actively use Claude and other AI assistants for data exploration, SQL development, analytical workflows, research, documentation, and automation
Explore opportunities to apply AI and machine learning approaches to forecasting, customer segmentation, anomaly detection, customer behavior analysis, and other business use cases
Translate complex data into clear business insights and actionable recommendations
Present key findings, trends, and recommendations to senior leadership

JOB QUALIFICATIONS
Bachelor’s degree in Statistics, Mathematics, Computer Science, Economics, or another quantitative field
Proven experience as a Data Analyst / Senior Data Analyst, preferably in e-commerce, retail, consumer goods, or a related industry
Strong proficiency in:SQL
Excel
Google Sheets
Power BI or other BI systems

Strong analytical and problem-solving skills with the ability to work with large and complex datasets
Strong interest in using AI tools to improve analytical productivity, automate workflows, and build scalable analytics solutions
Strong attention to detail and data accuracy
Excellent communication and presentation skills, with the ability to explain analytical findings to non-technical stakeholders
English level: Upper-Intermediate or higher

NICE TO HAVE
Experience with Python for data analysis, automation, or data processing
Experience with machine learning or predictive analytics, including forecasting, customer segmentation, propensity modeling, anomaly detection, or related use cases
Experience using Claude, ChatGPT, or other AI-powered tools as part of day-to-day analytical work
Experience building AI-assisted analytical workflows, internal tools, or automations

WORKING FORMAT
Full-time
Remote
Working hours: 16:00–01:00 Ukrainian time

WHAT OUR CLIENT OFFERS
Competitive compensation aligned with market standards
A stable full-time role in a fast-growing international business
Direct exposure to a high-growth U.S. e-commerce and retail environment
Opportunity to influence business decisions through data and analytics
Opportunity to work with and implement modern AI-powered analytics approaches
Professional growth and long-term collaboration
Remote-friendly working environment
Bonus and benefits package, with details discussed during the interview

See also

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