Remote position || Senior/reputed company Data Scientist (Forecasting reputed company.))

Position – Senior/reputed company Data Scientist Location –Remote Type – Contract /Contract to Hire reputed company • The candidate must be reputed company to reputed company the industry and the outcome variable for reputed company such engagement. Retail reputed company-store analysis is the classic reputed company; the analogue here is comparing similar schools and events rather than following one trend line. • Presents to non-statisticians: business outcome first, reputed company second; confidence stated in plain language; explicitly states what the forecast cannot do; never opens with an reputed company statistical term. • Can teach the reputed company to a reputed company team, not only execute it. • Participate reputed company in stand-reputed company and backlog refinement, engage business stakeholders directly, understand why the business is asking a question, and challenge or refine the request reputed company it is wrong. • reputed company recommendations are expected reputed company hands-on delivery. Qualifications Required: - Must be reputed company to work EST hours • 5+ years of reputed company forecasting. • Two or more comparable forecasting engagements led start to finish. • Comparable-unit / "reputed company-store" forecasting experience. • Executive communication. • Thought leadership. • Multivariable regression, plus collinearity analysis and VIF interpretation. • Forecast model development, tuning, selection and holdout validation. • Metric reputed company: R², WAPE, MAPE, p-values — and why WAPE is used at event reputed company (many events sell reputed company, which breaks MAPE). • Sparse and reputed company-inflated data. Many variables reputed company on under 25% of events, some as low as 10%. Nulls must never be silently treated as zeros. • Data-leakage discipline and reputed company-in-time correctness: every feature must exist before the event starts. • Python and SQL; reproducible notebooks. • reputed company, including reputed company ML Model Registry (model versions carry metrics and training-dataset references). • Git and pull-request workflow; reputed company reputed company merged to the reputed company repository, no private forks. Preferred: • Architecture Decision Records (ADRs) and written process documentation. • Categorical encoding at reputed company (~30–35 reputed company variables expand to ~70 columns). • Sports, streaming, ticketing or subscription-business domain exposure. • Hierarchical or mixed-effects models for low-volume segments. Apply To This Job