Note: The job is a remote job and is open to candidates in USA. Quantori is looking for a Senior Data Scientist to develop predictive models and analytical solutions that generate actionable insights and support business decision-making. The role focuses primarily on traditional machine learning using structured datasets, where you will own model development, experimentation, validation, and performance evaluation.
Responsibilities
- Develop predictive models that generate insights, recommendations, and business signals
- Perform data discovery, exploratory data analysis, feature engineering, and feature selection
- Build classification, regression, clustering, segmentation, recommendation, and forecasting models
- Design and execute model validation, experimentation, and backtesting methodologies
- Evaluate model performance and translate results into clear business recommendations
- Develop reusable modeling frameworks and reproducible Python workflows
- Work with data stored in Snowflake and transformations developed in dbt Cloud
- Partner with ML engineers to containerize, deploy, monitor, and improve models in production
- Support model retraining, performance monitoring, and continuous improvement
- Translate business questions into analytical hypotheses, measurable objectives, and practical solutions
- Communicate findings, assumptions, risks, and business implications to technical and non-technical stakeholders
- Collaborate with data engineers, ML engineers, product teams, and business stakeholders
Skills
- 6–8 years of experience in data science, applied machine learning, statistics, or a related field
- Strong Python and SQL skills
- Hands-on experience with traditional ML methods and libs (pandas, NumPy, scikit-learn, PyTorch)
- Strong knowledge of predictive modeling, statistical analysis, experimentation, and model evaluation
- Experience designing validation and backtesting frameworks
- Practical experience with Snowflake and cloud-based analytics platforms
- Experience taking models from experimentation through production deployment
- Familiarity with Docker, data engineering concepts, and MLOps practices
- Strong analytical thinking, communication, stakeholder management, and problem-solving skills
- Experience developing models that generate customer-level insights or recommendations
- Familiarity with AWS and dbt Cloud
- Knowledge of causal inference, experimentation, or optimization methods
- Exposure to generative AI, LLM-based applications, graph analytics, or RAG
- Experience in pharmaceutical, biotechnology, healthcare, or life sciences environments
Benefits
- Competitive compensation
- Flexible working hours
- Continuous education, mentoring, and professional development programs
- A team with excellent tech expertise
- Contract through the end of the year, with a possible extension based on project needs and performance
Company Overview