Decision Scientist

Fractal; San Francisco (CA); Remote; USD 85,000 - 130,000; Full time

Job summary

Fractal Analytics is hiring a Decision Scientist to join its Data Science organization in the Bay Area or New York, with remote work options. The role blends hands-on analytics with business understanding to frame questions, analyze performance, test hypotheses, and translate findings into actionable recommendations across physical retail, e-commerce, and omnichannel experiences for wearable products.

Key responsibilities include framing problems, analyzing retail performance, generating

Qualifications

• Strong quantitative and analytical problem-solving skills.
• Experience with statistical analysis, hypothesis testing, forecasting, experimentation, and causal analysis.
• Ability to structure ambiguous business questions into measurable analytical problems.

Responsibilities

• 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.
• 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.

Skills

Quantitative problem solving

Statistical analysis

Hypothesis testing

Forecasting

Experimentation

Causal analysis

Ambiguity framing

SQL

Python

Relational databases

AI tools

Data visualization

Tools

SQL

Python

Relational databases

AI tools

BI tools

Job description

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

Note

This position is not eligible for Immigration Sponsorship at this time

Location: Bay Area, CA or New York City, NY (Open to remote work)

Role Overview:

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.

Your work will support decisions across physical retail, e-commerce, and omnichannel experiences for next-generation wearable products.

Key Responsibilities:

• 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.
• 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.

Must-Have Skills:

Analytical & Decision Science

• Strong quantitative and analytical problem-solving skills.
• Experience with statistical analysis, hypothesis testing, forecasting, experimentation, and causal analysis.
• Ability to structure ambiguous business questions into measurable analytical problems.

Technical

• Proficiency in SQL and Python for data extraction, analysis, modeling, and automation.
• Experience working with relational and large-scale datasets.
• Familiarity with AI tools for accelerating analysis, automation, and insight generation.
• Experience with data visualization and BI tools.

Business Acumen

• Ability to connect analytical findings to practical business decisions.
• Understanding of common commercial metrics such as sales, revenue, conversion, demand, customer behavior, inventory, and channel performance.
• Ability to evaluate business opportunities and quantify potential impact.

Retail Domain (is a plus)

• Understanding of retail operations, consumer sales, e-commerce, or omnichannel environments.
• Familiarity with consumer electronics or wearable technology is a plus.
• Ability to explain analytical findings clearly to both technical and non-technical audiences.
• Experience collaborating with stakeholders across sales, marketing, product, and operations.
• Ability to translate analysis into concise, actionable recommendations.

Good-to-Have Skills

• Experience with A/B testing or experimentation.
• Exposure to causal inference techniques.
• Experience with sales or demand forecasting.
• Understanding of pricing and promotional analytics.
• Exposure to customer segmentation or propensity models.
• Understanding of supply chain and inventory analytics.
• Experience applying machine learning to commercial or retail use cases.Experience with AI-enabled or automated analytical workflows.

Pay:

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Fractal, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $85,000 - $130,000 with the potential for a higher base depending on experience, skills, and overall fit for the position. In addition, for the current performance period, you may be eligible for a discretionary bonus.

As a full-time employee of the company or as an hourly employee working more than 30 hours per week, you will be eligible to participate in the health, dental, vision, life insurance, and disability plans in accordance with the plan documents, which may be amended from time to time. You will be eligible for benefits on the first day of employment with the Company. In addition, you are eligible to participate in the Company 401(k) Plan after 30 days of employment, in accordance with the applicable plan terms. The Company provides for 11 paid holidays and 12 weeks of Parental Leave. We also follow a “free time” PTO policy, allowing you the flexibility to take the time needed for either sick time or vacation.

Fractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.