Data Scientist

Remote Role - Pittsburgh, PA Headquarters Office

Salary Range: $100K - $125K

About Us

Founded in Pittsburgh, PA by Carnegie Mellon University alumni, BlastPoint is a data-driven, AI based customer intelligence product company. We sell our proven SaaS based technology to mid-sized and large organizations. Our unique data-driven customer intelligence technology allows organizations to develop predictive, action-ready, objective-oriented insights: from developing customer strategies, to optimizing customer engagement, to enabling the overall customer journey. BlastPoint’s key differentiator is its highly targeted, objective-driven intelligence.

BlastPoint is growing rapidly (300%-400% YoY), and has multiple large customers already established (billion dollars +). BlastPoint is presently engaged with large utilities, insurance and banking institutions, as well as large automakers, including Electric Vehicle manufacturers and customers in other related industries. With our rapid growth and proven technology, we are looking to build our teams quickly for continued growth and expansion into multiple industries and countries.

Why You Should Work for Us

Focus: Everyone at BlastPoint is highly motivated and driven for success. BlastPoint’s unique technology has brought significant results to our customers, creating huge opportunities for growth and developing a brand in the customer intelligence domain. BlastPoint offers an open culture to its employees, allowing them to bring new ideas and offer freedom in achieving results and objectives.

Growth: BlastPoint is poised to make a difference in customer intelligence space and is at the brink of multifold growth. BlastPoint is a fit for anyone who wants to grow their career fast, take challenges, and make it big.

Solve Challenging Problems: Customer intelligence is required in every aspect of business. BlastPoint’s platform incorporates cutting-edge approaches to geospatial data, machine learning, psychographic clustering, data enrichment, and a dynamic visualization environment–all at scale.

Have An Impact: Small but mighty, BlastPoint’s growth is due to big companies increasingly trusting us with supporting key decisions using their most sensitive data. What we do positively impacts the lives of millions of Americans (and beyond).

Make Positive Change in the World: BlastPoint is all about green value. Our solutions reduce paper consumption, help struggling families pay their bills, and promote clean energy. We also offer our platform for free to nonprofits and civic-oriented organizations.

Employee-Focused Culture: We support the individual needs of our team, from schedule and time-off flexibility to generous compensation benefits. We also tailor growth opportunities, from skills training to industry conferences.

Job Description:

We are seeking an experienced Data Scientist to join our growing engineering team. The ideal candidate is adept at building practical, effective machine learning models to solve real-world problems. This role will focus on developing data-driven solutions, ensuring model quality, and enabling scalable workflows. The successful candidate will develop and deliver predictive models, improve the systems behind our modeling work, and collaborate with clients and internal teams to produce consistent, high-value results.

Primary 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 template 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.

Professional Requirements:

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.

Nice to Haves:

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:

Competitive Salaries
$500 Home Office Stipend
Health, Dental, and Vision Insurance
Work/Life Balance Culture
3 weeks of paid vacation
10 Paid Holidays
Unlimited Sick Time
401K

Our Values:

Everybody matters
We beat expectations
Innovation built on a foundation
Cards on the table, always
“The smartest systems from the most comprehensive data built by the best people”

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