Applied Scientist, Forecasting
Indexed description
This position is posted by Jobgether on behalf of a partner company. We are currently looking for an Applied Scientist, Forecasting in India.
You will join a highly analytical and mission-driven environment focused on building advanced forecasting systems that directly influence key business and strategic decisions. In this role, you will design and deploy statistical, econometric, and machine learning models to improve forecasting accuracy and reduce uncertainty across complex, large-scale datasets. You will work on end-to-end modeling challenges, from data preparation and feature engineering to model development, validation, and production deployment. The role requires strong collaboration with cross-functional teams including finance, product, engineering, and operations to translate predictive insights into actionable business strategies. You will also contribute to building scalable forecasting frameworks and tools used across the organization. This is a high-impact position suited for someone who thrives at the intersection of data science, economics, and real-world business problem-solving in a global, remote-first environment.
Accountabilities:
- Design, develop, and evaluate advanced statistical, econometric, and machine learning models for forecasting and prediction use cases.
- Build robust backtesting and validation frameworks to assess forecast accuracy, stability, and business impact.
- Own the end-to-end modeling lifecycle, including data exploration, feature engineering, model development, deployment, monitoring, and explainability.
- Translate complex forecasting outputs into clear, actionable insights and recommendations for senior stakeholders and leadership teams.
- Quantify uncertainty and communicate model assumptions, limitations, and trade-offs to both technical and non-technical audiences.
- Partner with cross-functional teams such as finance, product, engineering, marketing, and operations to scale forecasting solutions.
- Improve and maintain shared forecasting tools, data pipelines, and analytical frameworks used across the organization.
- Collaborate with other applied scientists and data scientists to solve complex business and domain-specific problems using advanced analytics.
- Advanced degree (Master’s or PhD) in Economics, Statistics, Operations Research, Data Science, Computer Science, Mathematics, Econometrics, or a related quantitative field.
- 3+ years of experience in applied science, data science, or quantitative modeling roles.
- Strong expertise in time-series forecasting, econometric modeling, nowcasting, or similar predictive techniques.
- Proven experience building and deploying machine learning or statistical models in production environments.
- Strong programming skills in Python and SQL for data analysis, modeling, validation, and deployment.
- Solid understanding of data engineering principles and ability to work with large-scale, complex datasets.
- Ability to work with noisy, incomplete, or delayed real-world data while designing robust modeling approaches.
- Strong communication skills with the ability to explain complex analytical concepts to non-technical stakeholders.
- Experience collaborating in cross-functional, fast-paced environments and influencing data-driven decisions.
- Strong analytical mindset with attention to detail and a strong focus on business impact.
- Fully remote-first working model with flexible work arrangements
- Competitive compensation package with performance-based incentives
- Opportunity to work on large-scale forecasting systems with real business impact
- Exposure to advanced machine learning, econometrics, and production-grade data science
- Collaborative, global work environment with cross-functional teams
- Strong focus on learning, innovation, and career development
- Inclusive and supportive culture promoting flexibility and autonomy
- Work on high-impact projects influencing strategic decision-making at scale
Requirements:
Benefits:
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