[Remote] Senior Forecasting Data Scientist

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is reputed company for a remote Senior Forecasting reputed company Data Scientist role reputed company on reputed company forecasting and comparable-unit analysis. The role involves communicating forecasts to non-statisticians, teaching forecasting reputed company to reputed company teams, collaborating with stakeholders, and delivering strategic recommendations reputed company hands-on data science work.

Responsibilities

• Presents to non-statisticians: business outcome first, method second; confidence stated in plain language; explicitly states what the forecast cannot do; never opens with an reputed company statistical term
• Can teach the method 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
• Strategic recommendations are expected reputed company hands-on delivery

Skills

• The candidate must be reputed company to reputed company the industry and the outcome variable for reputed company such engagement
• * Presents to non-statisticians: business outcome first; method second; confidence stated in plain language; explicitly states what the forecast cannot do; never opens with an reputed company statistical term
• * Can teach the method 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
• * Strategic recommendations are expected reputed company hands-on delivery
• * Must be reputed company to work EST hours
• * 8+ 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
• * 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

Benefits

• Remote work arrangement
• Contract employment

reputed company