Data Scientist - TIme Series

Data Scientist - TIme Series at Acunor Data Scientist - TIme Series at Acunor in Gloucester City, New Jersey Posted in 1 day ago.

Type:

full-time

Job Description:

Senior Data Scientist -

Econometrics & Time Series Location:

Philadelphia, PA (Hybrid - 2-3 Days Onsite)

Type:

Full-Time Role Overview We are seeking a Senior Data Scientist with strong expertise in Econometrics and Time Series Analysis to support advanced analytics initiatives for a large Telecommunications environment. This role focuses on forecasting, causal inference, customer behavior analytics, and statistical modeling using large-scale datasets. The ideal candidate will have deep hands-on experience with econometric techniques, probabilistic modeling, and time series forecasting frameworks, along with strong Python and SQL skills. Key Responsibilities Build and deploy advanced time series forecasting models including ARIMA, SARIMA, VAR, and state-space models Apply econometric techniques such as WLS, regression diagnostics, panel data models, and causal inference methods Develop Bayesian and probabilistic models for uncertainty estimation and decision-making Utilize Markov chains and stochastic modeling techniques for behavioral and sequential data analysis Translate complex business problems into scalable analytical solutions and actionable insights Work with large-scale datasets using Databricks and modern analytics platforms Partner with business and technical stakeholders to drive data-driven decision making Mentor junior data scientists and promote best practices in statistical modeling and experimentation Required Skills Strong expertise in Econometrics and Time Series Analysis Hands-on experience with: ARIMA, SARIMA, VAR, forecasting models Regression diagnostics, WLS, panel data models Causal inference and experimentation frameworks Bayesian statistics and probabilistic modeling Markov chains and stochastic processes Strong programming skills in Python and SQL Experience with Databricks or similar big data environments Excellent communication and stakeholder management skills Nice to Have Experience with machine learning models and predictive analytics Knowledge of feature engineering, model validation, and performance tuning Exposure to ML pipelines and MLOps concepts Telecommunications domain experience is a plus