Junior Data Scientist

Responsibilities

• Designs, builds, and delivers analytical solutions that support underwriting, pricing, and operational decision-making.
• Performs exploratory data analysis, feature engineering, data pipeline development, and predictive modeling, working closely with business and technical partners to ensure solutions are accurate, scalable, and aligned with business goals.
• Partner with business stakeholders to define analytical needs and prototype solutions.
• Evaluate the business value of internal and third-party data sources using standardized assessment criteria.
• Build foundational understanding of relevant insurance and energy domain concepts.
• Data Discovery, Exploration & Engineering
• Conduct Exploratory Data Analysis to assess data quality, structure, coverage, and predictive potential.
• Build and refine data pipelines using SQL and Python.
• Develop entity-matching methods, including geospatial and temporal techniques.
• Engineer and maintain features that support analytical and predictive modeling.
• Model Development & Experimentation
• Build and evaluate predictive models, comparing performance against benchmarks.
• Quantify expected business value, costs, and ROI for proposed solutions.
• Design repeatable workflows for modeling, experimentation, and evaluation.
• Deployment, Integration & Monitoring
• Collaborate with engineering teams to integrate analytical models into production systems.
• Implement monitoring to ensure data and model quality over time.
• Identify opportunities for iteration and performance improvement based on results and business feedback.
• Collaboration, Communication & Project Delivery
• Work with cross-functional teams to clarify requirements and acceptance criteria.
• Prepare analytical datasets, dashboards, and reports that support decision-making.
• Communicate insights clearly to technical and non-technical stakeholders.
• Quality, Documentation & Automation
• Conduct quality assurance checks on datasets, metrics, and models.
• Maintain documentation for data sources, features, models, and workflows.
• Automate repetitive or manual tasks using scripting and AI tooling.

Qualifications

• Experience & Professional Skills: 2–5 years of experience in data science or a related analytical field, including exposure to model deployment and monitoring.
• Strong sense of ownership, urgency, and self-motivation; Excellent written and verbal communication skills; able to convey complex concepts clearly.
• Effective collaborator with experience in cross-functional, team-oriented environments.
• Prior quantitative research experience through academic work, personal projects, or previous roles.
• Technical Skills: Proficiency in Python (pandas, NumPy, scikit-learn) and SQL; solid understanding of databases and data modeling.
• Experience conducting exploratory data analysis, including profiling, handling missing data, and outlier detection.
• Feature engineering experience, including geospatial, temporal, and derived features.
• Familiarity with version control (e.g., GitHub) and cloud analytics platforms (e.g., Databricks).
• Understanding of Agile or SDLC practices.
• Domain Knowledge: Familiarity with Oil & Gas or Property & Casualty insurance concepts is a plus.

Qualifications

• Educational Background: Master’s degree in data science, analytics, statistics, computer science, engineering, or related field.

Additional Company Details

• We do not accept any unsolicited resumes from external recruiting agencies or firms.
• The company offers a competitive compensation plan and robust benefits package for full-time regular employees.
• The actual salary for this position will be determined by a number of factors, including the scope, complexity and location of the role; the skills, education, training, credentials and experience of the candidate; and other conditions of employment.

Additional Requirements

• Location and Travel: Primary location Houston, TX. Sponsorship Details: Sponsorship not Offered for this Role.