Remote Monte Carlo Simulation Jobs (NOW HIRING)

The Role
We're looking for a full-stack, product-minded Senior Data Scientist to help build a new greenfield product at Fusion. This work will unify resilience data from some of the
world's largest and most systemically important organizations-and help define the future research and analytics for an entire industry.
This role sits at the intersection of graph analytics, predictive modeling, and product development. You'll work with network-structured data-operational dependencies,
recovery sequences, supply chain relationships-and apply advanced analytical techniques to problems where the structure of connections between entities matters as
much as the entities themselves.
This is a high-ownership role for someone who wants to work close to customers, shape product direction, and apply graph-aware analytics and modeling techniques to real-world, high-impact problems.
Key Responsibilities
• Partner closely with customers and internal product teams to design and build the first in a new line of data products powered by a graph-backed resilience platform.
• Develop and apply network analysis and graph-based analytical techniques to model operational dependencies, identify critical nodes, assess cascading failure risks, and optimize recovery sequences.
• Own and evolve existing analytical products involving Monte Carlo simulation, Bayesian networks, optimization (linear and constraint programming), and generative capabilities.
• Design and build entity resolution models that match and link records across disparate customer data sources-using probabilistic, deterministic, or ML-assisted approaches.
• Contribute to predictive intelligence initiatives, including models for threat and risk scoring, escalation prediction, and recovery time estimation that improve through feedback loops.
• Contribute to internal analytics initiatives, including maintaining and improving our predictive churn model and supporting product and usage analytics.
• Help influence product direction by identifying opportunities where graph analytics, modeling, or automation can meaningfully improve customer outcomes.
Skills & Requirements
Knowledge, Skills, and Abilities
• Product-minded approach with the ability to learn new domains quickly, develop deep empathy for customer problems, and translate those needs into impactful data solutions.
• Experience with or strong interest in network analysis, graph analytics, or problems where relationships between entities are central-e.g., dependency mapping, supply chain risk, social network analysis, fraud detection, knowledge graphs, or similar domains.
• Familiarity with graph concepts (centrality measures, community detection, shortest path, cascading failure analysis) and comfort reasoning about data as networks rather than flat tables.
• Experience with entity resolution, record linkage, or deduplication-whether using probabilistic matching frameworks, ML-based approaches, or rules-based systems.
• Strong data storytelling skills, with the ability to turn complex network-based analyses into clear, compelling dashboards and visualizations for both technical and non- technical audiences.
• Comfort working across the data science stack, including production-grade SQL, transformation pipelines, simulation, optimization, machine learning, and emerging intelligent functionality.
• Technical generalist mindset with enthusiasm for learning new tools, languages, and platforms.
• Familiarity with AI-assisted development and analysis tools (e.g., Copilot, Cursor, Claude Code, or similar) and comfort using them to accelerate data science and engineering workflows.
• Strong SQL skills and familiarity with Python; Java experience is a plus.
• Experience collaborating closely with customers or customer-facing teams and taking ownership of translating real-world problems into data-driven solutions.
Qualifications (Education and Experience)
• Bachelor's degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field.
• 5+ years of experience in data science, machine learning modeling, and data products.
• Experience delivering value-creating data products for end users.
• Experience with graph or network-structured data in a professional, research, or academic setting (strongly preferred).
• Experience with entity resolution or record-matching techniques (nice to have).
• Exposure to simulation, optimization, or operations research techniques (nice to have).
• Experience building or maintaining machine learning models, including predictive scoring or classification models (nice to have).
• Experience working with Salesforce data or platforms (nice to have).
Milestones for the First Six Months
In one month, you will:
- Complete all HR and onboarding requirements
- Become familiar with Fusion's industry, data strategy, graph data model, tools, and products
- Begin contributing to existing analytics or product initiatives with guidance
In three months, you will:
- Begin agile development of our new greenfield product, including graph-based analytical features, in concert with our partners
- Collaborate with customers and partners to iterate on entity resolution and network analysis capabilities
- Commit tightly scoped enhancements to existing data science products
In six months, you will:
- Own and deliver the first version of our new data product, including graph analytics and predictive features
- Directly manage and incorporate feedback from customers and function as a data product owner
- Consistently meet delivery expectations with minimal oversight
- Propose new enhancements and products leveraging graph intelligence and feedback-loop-driven models
Compensation & Benefits
The annual base salary range for this position is $145,000-$160,000, depending on the candidate's experience, qualifications, and relevant skill set. The position is also eligible for an annual bonus. Fusion offers a comprehensive benefits package including medical, dental, vision, and a 401(k) plan.
Disclaimers
Fusion is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, age, pregnancy, military service or discharge status, genetic information, sex, sexual orientation, gender identity, or national origin. Nothing in this job posting should be construed as an offer or guarantee of employment.