Hands-On Engineering Leader AI Engineering-Predictive AI/Forecasting

Job description

At Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market. What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture. Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform. Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small. Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together! Job Description Senior Hands-on Engineering Leader – Predictive AI & Forecaster Position Summary We are seeking a highly skilled Senior Hands-on Engineering Leader – Predictive AI & Forecasting to design, develop, and implement advanced predictive models and forecasting solutions for complex business challenges. The ideal candidate will possess strong expertise in statistical modeling, machine learning, predictive analytics, and time-series forecasting, with a proven track record of delivering solutions from initial problem formulation to production deployment and measurable business impact. This role demands a blend of advanced analytical skills, software engineering discipline, business acumen, and scientific rigor. The individual will independently address complex data science problems, evaluate methodologies, and create scalable, reliable, and interpretable predictive solutions. Key Responsibilities Predictive AI & Advanced Analytics • Design, develop, validate, and deploy predictive models for complex business challenges. • Utilize advanced statistical and machine learning techniques to forecast outcomes, behaviors, risks, and business events. • Create solutions for regression, classification, risk prediction, anomaly detection, and behavioral prediction. • Identify significant predictive signals from large-scale datasets. • Develop models that enhance data-driven decision-making and yield measurable outcomes. • Assess model performance using statistical measures and relevant business KPIs. • Implement model explainability, interpretability, and uncertainty estimation techniques. Time Series Forecasting • Lead the development of advanced forecasting solutions for various time-series data. • Generate forecasts based on business needs. • Analyze trends, seasonality, cyclicality, and temporal dependencies. • Address forecasting challenges such as missing observations and changing patterns. • Develop and evaluate statistical, machine learning, and hybrid forecasting approaches. • Incorporate relevant exogenous variables into forecasts. Statistical & Machine Learning Modeling • Select and apply suitable modeling techniques based on data characteristics and business needs. • Utilize methods including ARIMA, Exponential Smoothing, Regression, Random Forest, and LSTM. • Establish baseline models and demonstrate improvements through experimentation. Data Preparation & Feature Engineering • Conduct exploratory and statistical analysis of datasets. • Create robust temporal and predictive features. • Identify and resolve data quality issues. • Integrate internal and external data sources to enhance performance. • Develop scalable methods for feature generation. Model Validation & Evaluation • Establish rigorous model development and validation methodologies. • Implement time-aware cross-validation and backtesting as necessary. • Evaluate models using metrics like MAE, RMSE, and Precision. • Conduct residual and sensitivity analysis. • Ensure controls are in place to prevent data leakage. Productionization & MLOps • Translate data science solutions into reliable production systems. • Collaborate with cross-functional teams to operationalize models. • Develop production-ready workflows for training and inference. • Monitor model accuracy and support automated retraining. • Ensure solutions are maintainable and scalable. Technical Leadership & Collaboration • Lead data science initiatives from problem definition to implementation. • Provide technical guidance on predictive modeling and analytical approaches. • Translate business needs into data science solutions. • Communicate findings to technical and non-technical audiences. • Mentor Data Scientists and contribute to best practices. • Evaluate emerging technologies in Predictive AI and machine learning. Required Qualifications • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Operations Research, or Economics. • More than 15 years professional experience and 10+ years of experience in Data Science, Machine Learning, or a related area. • Hands-