Data Scientist - Time Series Forecasting & Modeling (3-5 yrs)

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!