Director & Data Scientist developing statistical and machine learning solutions for actuarial pricing within Employee Benefits. Collaborating with cross - functional teams to shape future data - driven strategies.
About the role
- Data Scientist developing AI systems for Parspec’s platform transforming construction materials supply chain. Analyzing unstructured datasets and building scalable data pipelines for enhanced recommendations.
Responsibilities
- Work with large, messy, and unstructured datasets, transforming them into structured formats that improve model performance
- Gather, clean, and structure datasets from multiple sources to support AI training pipelines
- Build systems that enable the team to maintain high-quality datasets and drive model accuracy over time
- Analyze complex datasets to identify patterns, trends, and insights that improve product discovery and recommendations
- Design and build end-to-end data pipelines and machine learning pipelines
- Develop scalable systems capable of handling large volumes of construction product data
- Work with engineering teams to deploy models into production systems
- Work closely with product managers, designers, and engineers to integrate AI capabilities into Parspec’s applications
- Own product features from concept through implementation and deployment
- Communicate technical findings through visualizations, reports, and dashboards that support product and business decisions
- Stay current with the latest developments in machine learning, deep learning, and AI frameworks
- Contribute to Parspec’s broader AI research and development initiatives
- Uphold Parspec’s culture of engineering excellence through high-quality code and thoughtful system design
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Statistics, or a related technical field
- Strong conceptual understanding of machine learning, statistics, and data modeling
- Proven experience working with large, messy, or unstructured datasets, including cleaning, structuring, and transforming data for analysis and model training
- Strong programming skills in Python and SQL (R is a plus)
- Experience implementing machine learning projects using libraries such as NumPy, Pandas, scikit-learn, and Matplotlib
- Experience training deep learning models using TensorFlow/Keras or PyTorch
- Strong knowledge of statistics, probability, and machine learning techniques such as regression, classification, and clustering
- Ability to write clean, efficient, and maintainable code
- Ability to take ownership of projects and drive initiatives from concept through production deployment
- Experience building data pipelines and ML pipelines for production systems (preferred)
- Familiarity with AWS infrastructure and Django-based applications (preferred)
- Experience working with OCR pipelines, document processing, or PDF data extraction (preferred)
- Familiarity with data visualization tools such as Tableau or Power BI (preferred)
- Strong knowledge of algorithms and data structures (preferred)
- Participation in Kaggle competitions, competitive programming, or open-source contributions (preferred)
- Experience collaborating with distributed teams across multiple time zones (preferred)
Benefits
- Competitive salary and benefits, including family insurance coverage, free health teleconsultations, and learning/upskilling budgets
- Equity in the company
- Flexible hours and a hybrid work setup
- Unlimited PTO
- Opportunity to grow with a fast-scaling company transforming a large market
Job title
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Degree requirement
Tech skills
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