MissionOG · 14 hours ago
Data Scientist (Remote - United States)
United States
Full-time
Remote
Entry, Mid Level
2+ years expBlastPoint is a data-driven, AI-based customer intelligence product company founded by Carnegie Mellon University alumni. They are seeking an experienced Data Scientist to develop data-driven solutions and machine learning models, ensuring model quality and enabling scalable workflows for their clients.
B2BFinancial ServicesVenture Capital
Responsibilities
Develop machine learning models using customer, open-source, and proprietary data for a variety of business cases
Contribute to the design and automation of customer data analysis and insights delivery processes
Develop new ML solutions for emerging use cases, client needs, or market demand, and standardize and templatize these approaches into data products
Serve as the technical liaison between the customer and the product, ensuring tools are effective, gathering feedback, and customizing solutions based on client requirements
Serve as the technical liaison between the customer and the product, ensuring tools are effective, gathering feedback, and customizing solutions based on client requirements
Apply empathy and an analytical perspective when consulting with clients, understanding their unique needs, and representing them internally and externally. This involves participating in client meetings, conducting technical discussions, presenting project outcomes, and engaging in customer-facing technical interactions as needed
Dedicate 60-80% of your time to client projects, 20-40% to developing internal tools or data products, and approximately 10% to account management or support tasks. The aim is to leverage client feedback to make our systems more efficient and self-service, reducing the reliance on consultative project teams
Qualification
Required
2–4 years of experience in data science, machine learning, or predictive analytics; Bachelor's degree or equivalent experience in a relevant field
Highly proficient in Python, including Pandas, Scikit-Learn, and modular ML workflows built around reproducible pipelines. Experience working within shared codebases or contributing to internal tools that support other data scientists or analysts
Strong ML modeling fundamentals and experience translating business problems into machine learning or predictive analytics solutions. Knowledge of different machine learning and statistical techniques, including their strengths, limitations, and appropriate use cases
Practical experience developing ML models from exploration to validated, working solutions, with sound judgment about feature design, evaluation metrics, and iterative improvement. Experience contributing to model deployments or maintaining models in production environments is highly valued
Excellent communication skills, with the ability to present technical information to non-technical audiences
Comfort working in a fast-paced environment with a mix of client work and internal initiatives. Self-directed and organized—able to manage your own workload and proactively flag risks or blockers
A curious and proactive problem solver, open to sharing new ideas, advocating best practices, and self-teaching as needed
Authorized to work in the United States
Preferred
Familiarity with AWS cloud services, with a particular focus on Amazon SageMaker and its core functionalities for building, training, and deploying machine learning models
Deep skillset in advanced ML model interpretation methods (e.g., SHAP, partial dependence plots, other feature attribution techniques) and proven ability to articulate ML concepts, model behavior, and their implications to diverse audiences
Prior contributions to open-source or internal Python libraries that provide reusable components for data processing, modeling, or analytical workflows
Strong data visualization skills, with experience creating publication-quality visuals for high-visibility reports and a proven ability to convey complex insights from data clearly and effectively
Experience with time-series modeling, NLP, or recommendation systems
Willingness to travel domestically for company events (2-4 times per year)
Benefits
Schedule and time-off flexibility
Generous compensation benefits
Skills training
Industry conferences
Company
MissionOG
MissionOG provides capital to early and growth stage B2B technology companies.
2-10 employees
Funding
Current Stage
Early StageLeadership Team
Andy Newcomb
Co-Founder and Managing Partner
Gene Lockhart
Chairman, Co-Founder & Managing Partner
Recent News
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2025-11-07
2025-11-06
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