Senior Data Scientist

EXL Talent Acquisition Team; United States; On-site; USD 120,000 - 170,000; Full time

Job summary

EXL Talent Acquisition Team is seeking a data scientist lead to champion time series forecasting, using ARIMA, VAR, and state-space approaches to drive strategic decisions.

You will apply econometric techniques, design Bayesian models for uncertainty estimation, and work with large datasets in Databricks, mentoring juniors across cross-functional teams.

This role demands translating business problems into robust analytical solutions and delivering actionable insights with stakeholders.

Qualifications

• Experience building time series forecasts (ARIMA, VAR, state-space).
• Knowledge of econometric methods for business problems.
• Experience designing Bayesian models for uncertainty estimation.
• Familiarity with Markov chains and stochastic processes.
• Ability to work with large datasets in Databricks.

Responsibilities

• Lead development of time series forecasting models for business-critical use cases.
• Apply econometric techniques to solve real-world problems.
• Design and implement Bayesian models for uncertainty estimation and decision-making.
• Utilize Markov chains for sequential data modeling.
• Translate business problems into robust analytical frameworks and deliver insights.
• Work with large datasets using Databricks.
• Collaborate with stakeholders to ensure model relevance and impact.
• Mentor junior team members and promote best practices in modeling and experimentation.

Skills

Time series forecasting

Econometrics

Bayesian modeling

Markov chains

Databricks

Leadership

Tools

Databricks

Job description

Key Responsibilities

• Lead development of time series forecasting models (ARIMA, VAR, state-space models, etc.) for business-critical use cases.
• Apply econometric techniques such as WLS, panel data models, and causal inference methods to solve real-world business problems.
• Design and implement Bayesian models and probabilistic frameworks for uncertainty estimation and decision-making.
• Utilize Markov chains and stochastic processes for modeling sequential or behavioral data.
• Translate business problems into robust analytical frameworks and deliver actionable insights.
• Work with large datasets using Databricks
• Collaborate with stakeholders across business and technical teams to ensure model relevance and impact.
• Mentor junior team members and drive best practices in statistical modeling and experimentation.