Data Scientist - Time Series Forecasting & Modeling

Role : Data Scientist - Time Series Forecasting and Modeling Overview : We are seeking a skilled and experienced Data Scientist specializing in time series forecasting and modeling to join our analytics team. The ideal candidate will have a strong background in data analysis, statistical modeling, and machine learning, with a proven ability to apply these skills to solve complex business problems. You will be responsible for building, validating, and maintaining time series models to support business decision-making and operational efficiency. Key Responsibilities : - Develop, implement, and maintain time series forecasting models to predict trends, demands, or other key business metrics. - Analyze and preprocess large datasets, ensuring data quality and preparing inputs for modeling. - Apply advanced statistical techniques and machine learning methods to improve forecast accuracy. - Collaborate with cross-functional teams (e.g., finance, operations, supply chain) to understand business needs and deliver actionable insights. - Research and experiment with state-of-the-art algorithms, including ARIMA, SARIMA, LSTM, Prophet, and other statistical/machine learning methods for time series forecasting. - Conduct exploratory data analysis to identify trends, patterns, seasonality, and anomalies in time series data. - Communicate findings and model outputs through clear visualizations, reports, and presentations to both technical and non-technical stakeholders. - Monitor model performance, implement improvements, and maintain version control of modeling pipelines. - Automate workflows and integrate forecasting models into existing business systems. Qualifications : Required Skills and Experience : - Proven experience (3 years) in time series forecasting and modeling, including work with tools like Python, R, or similar platforms. - Strong knowledge of statistical methods, including ARIMA, SARIMA, ETS, and advanced machine learning techniques like neural networks (e.g., LSTM, GRU). - Experience with data visualization tools such as Tableau, Power BI, Matplotlib, or Seaborn. - Proficiency in handling and analyzing large datasets, including working with databases (SQL, NoSQL) and big data frameworks (Hadoop, Spark). - Familiarity with tools and libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. - Strong understanding of time series evaluation metrics (e.g., RMSE, MAE, MAPE) and techniques for hyperparameter tuning. - Solid programming and scripting skills (Python preferred, with knowledge of R, SAS, or similar tools). - Experience with version control tools (e.g., Git) and deployment workflows. Preferred Qualifications : - Advanced degree (Master's or Ph.D.) in Data Science, Computer Science, Mathematics, Statistics, or a related field. - Familiarity with business domains such as retail, finance, energy, or supply chain where time series forecasting is critical. - Experience in cloud platforms like AWS, Azure, or Google Cloud, specifically their data and ML tools. - Knowledge of anomaly detection, multivariate time series modeling, and causality analysis. Soft Skills : - Excellent problem-solving and critical-thinking skills. - Strong communication skills, capable of translating technical findings into actionable business insights. - Ability to work independently and collaboratively in a fast-paced environment. - Strong attention to detail and a commitment to delivering high-quality solutions. What We Offer : - Competitive salary and benefits. - Opportunities for professional growth and development. - A collaborative and innovative work environment. - Access to cutting-edge tools and technologies. If you are passionate about data-driven decision-making and have a knack for uncovering trends in time series data, we'd love to hear from you (ref:hirist.tech)

Location: in, IN

Posted Date: 11/27/2024