Company Details: Responsibilities:

• 
  Business Understanding & Solution Design
• 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.

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  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

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