Data Scientist - Time Series Forecasting

Company Overview :

Tiger Analytics is a global leader in AI and advanced analytics, helping enterprises solve complex business problems through data-driven decision-making. Operating at the intersection of data science, engineering, and business strategy, the firm partners with Fortune 500 companies across retail, CPG, insurance, and financial services. With a focus on delivering scalable, production-grade AI solutions, Tiger Analytics fosters a culture of deep technical expertise, continuous learning, and collaborative problem-solving, maintaining a significant footprint in major technology hubs like Bangalore.

Role Overview :

As a Data Scientist specializing in Time Series Forecasting, you will lead the design and implementation of sophisticated predictive models that drive strategic planning for our global clients. You will work closely with cross-functional teams of data engineers, consultants, and business stakeholders to translate complex business requirements into robust forecasting frameworks. By leveraging high-dimensional data, you will directly influence inventory optimization, demand planning, and revenue forecasting, ensuring that our clients maintain a competitive edge through precise, data-backed foresight.

Key Responsibilities :

- Architect and deploy advanced time series forecasting models to solve complex supply chain and demand planning challenges for enterprise clients.

- Collaborate with stakeholders to define business objectives, ensuring that model outputs align with operational goals and drive measurable financial impact.

- Lead the end-to-end lifecycle of machine learning projects, from data exploration and feature engineering to model validation and production deployment.

- Mentor junior team members by conducting code reviews and sharing best practices in statistical modeling and machine learning architecture.

- Communicate technical findings and model performance metrics to non-technical leadership to facilitate informed decision-making.

- Optimize existing forecasting pipelines to improve accuracy, scalability, and computational efficiency in cloud-based environments.

Required Skillset :

- Demonstrated expertise in building and tuning time series models, including ARIMA, ETS, Prophet, DeepAR, and transformer-based architectures.

- Proficiency in Python or R, with a strong command of machine learning libraries such as Scikit-Learn, TensorFlow, or PyTorch.

- Advanced understanding of statistical concepts, including stationarity, seasonality, autocorrelation, and error metric evaluation.

- Proven ability to translate ambiguous business problems into structured analytical frameworks, demonstrating strong interpersonal and stakeholder management skills.

- Experience working with large-scale datasets in cloud environments such as AWS, Azure, or GCP, and familiarity with SQL for data extraction and manipulation.

- A Master's degree or PhD in Statistics, Mathematics, Computer Science, or a related quantitative field from a premier institute.

- Ability to thrive in a hybrid work environment in Bangalore, balancing independent research with collaborative team initiatives.

- A minimum of 6 to 10 years of professional experience in data science, with a specific focus on forecasting or predictive modeling.