- Company Name
- ETQ
- Job Title
- Principal Data Scientist (AI)- REMOTE (US)
- Job Description
-
**Job Title**
Principal Data Scientist (AI) – Remote (US)
**Role Summary**
Lead advanced analytics for the ETQ division, developing and deploying machine‑learning models that solve complex business problems, driving product strategy, and delivering measurable impact across cross‑functional teams.
**Expactations**
- Own end‑to‑end model lifecycle from data acquisition to production deployment.
- Mentor and guide junior data scientists and analysts.
- Translate ambiguous business challenges into scalable analytical solutions.
- Communicate findings to executives and technical stakeholders, ensuring clarity and actionable insights.
**Key Responsibilities**
- Collect, clean, and analyze large multi‑source datasets.
- Design, develop, and evaluate predictive models, time‑series, and anomaly detection algorithms.
- Build model explainability (SHAP, LIME) for user confidence.
- Lead A/B and multivariate experiments, assess statistical significance, and report impact.
- Create dashboards, reports, and visualizations (Tableau, Power BI, matplotlib).
- Collaborate with product, engineering, and business leaders to implement data‑driven strategies for engagement, retention, and customer experience.
- Ensure data integrity, scalability, and reproducibility across environments.
- Stay current on ML, AI, and big‑data advancements; recommend technology adoption.
**Required Skills**
- Programming: Python or R; SQL expertise.
- Machine‑learning frameworks: scikit‑learn, XGBoost, LightGBM, TensorFlow/PyTorch, Prophet, LSTM.
- Experimentation: A/B testing, statistical analysis, hypothesis testing.
- Visualization: Tableau, Power BI, matplotlib, seaborn.
- Big‑data tools: Spark, Hadoop, Databricks, Snowflake (preferred).
- Cloud platforms: AWS, GCP, or Azure (preferred).
- Agile development: Jira, CI/CD pipelines.
- Strong statistical foundation (probability, inference, regression, classification).
- Problem‑solving and communication skills for technical and non‑technical audiences.
**Required Education & Certifications**
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
- Minimum 5 years of professional experience as a Data Scientist, Machine‑Learning Engineer, or equivalent role.
- Valid certifications relevant to data science or cloud ML (e.g., Certified Data Scientist, AWS Certified Machine Learning – Specialty, GCP Professional Data Engineer) are preferred.