A.I.-driven customer intelligence tools that give companies the power to discover & engage the humans in their data.

Data Scientist

Data ScientistData ScientistFull TimeRemoteTeam 11-50H1B No SponsorCompany Site LinkedIn

Location

United States

Posted

98 days ago

Salary

$100K - $125K / year

Bachelor Degree2 yrs expEnglishPandasPythonScikit Learn

Job Description

• 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. • 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.

Job 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.