Decision Scientist

Fractal Analytics is a strategic analytics partner to the most admired Fortune 500 companies globally and helps them power every human decision in the enterprise by bringing analytics & AI to the decision-making process. Fortune 500 companies recognize analytics as a competitive advantage to understand customers and make better decisions. We deliver insight, innovation, and impact to them by leveraging Big Data, analytics and technology and help them drive smarter, faster, and more accurate decisions in every aspect of their business.

Fractal has consistently been rated as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute. Fractal has been featured as a leader in the Customer Analytics Service Providers Wave™ 2019 by Forrester Research, and recognized as an “Honorable Vendor” in 2019 magic quadrant for data & analytics by Gartner.

Please visit Fractal | Intelligence for Imagination for more information about Fractal

This position is not eligible for Immigration Sponsorship at this time

As the retail landscape evolves with the growth of next-generation wearable technologies, data-driven decision-making is becoming increasingly important across sales, marketing, and retail operations.

We are seeking a Decision Scientist to join our Data Science organization and support business teams in solving complex retail and commercial problems using data, statistics, and structured analytical approaches.

This is a techno-functional role that combines hands-on analytics with strong business understanding. You will work closely with sales, retail operations, marketing, product, and other cross-functional teams to frame business questions, analyze performance, test hypotheses, evaluate opportunities, and translate findings into actionable recommendations
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Your work will support decisions across physical retail, e-commerce, and omnichannel experiences for next-generation wearable products.

• Frame business problems: Translate sales, marketing, and retail questions into clear analytical problems, hypotheses, metrics, and measurement approaches.
• Analyze retail performance: Evaluate sales, conversion, customer, product, store, inventory, and channel performance to identify trends, drivers, and improvement opportunities.
• Generate actionable insights: Use quantitative analysis to understand what is happening, why it is happening, and what actions could improve outcomes
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• Evaluate business opportunities: Assess growth levers such as pricing, promotions, customer targeting, channel performance, product mix, and retail execution.
• Support experimentation: Help design and analyze A/B tests, pilots, and other test-and-learn initiatives to measure the incremental impact of business interventions.
• Develop forecasts and scenarios: Build analytical models to evaluate potential outcomes and support decisions related to sales, demand, promotions, and retail performance.
• Build decision-support solutions: Develop dashboards, analytical tools, and lightweight decision models that enable business teams to monitor performance and make informed decisions.
• Communicate recommendations: Convert analytical findings into clear business narratives, recommendations, and visualizations for business and cross-functional stakeholders.
• Automate analytics: Use Python, SQL, AI tools, and automation to improve recurring analyses, reporting, and analytical workflows.
• Measure impact: Define appropriate KPIs and measurement frameworks to track whether implemented recommendations deliver the intended business outcomes.

• Strong quantitative and analytical…