Data Science Lead
Gurugram, Haryana, India
- Pay
- Pay not listed
- Work setting
Hybrid — work setting source
Work setup in the employer’s listing: Hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s listing: Full time
From the employer’s posting
What you’ll work on
Full postingLead development of time series forecasting models (ARIMA, VAR, state-space) for business-critical uses
Apply econometric and causal inference methods such as WLS and panel data models
Design Bayesian and probabilistic models for uncertainty estimation and decisions
Use Markov chains and stochastic processes to model sequential or behavioral data
Mentor junior team members and set best practices in statistical modeling
From the employer’s posting
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.
Mentor junior team members and drive best practices in statistical modeling and experimentation.
What you’ll bring
All qualificationsCore experience
- Strong foundation in econometrics and time series analysis
- Hands-on time series models (ARIMA, SARIMA, VAR) and forecasting
- Causal inference, including A/B testing and quasi-experimental methods
- Bayesian statistics and probabilistic modeling
Qualification wording
Strong foundation in econometrics and time series analysis (this is critical for the role).
Time series models (ARIMA, SARIMA, VAR, forecasting techniques)
Causal inference (A/B testing, quasi-experimental methods)
Bayesian statistics and probabilistic modeling
Tools in this posting
- SQL
- Databricks
- Python
Source — Tool mentions in context
- Markov chains or stochastic modeling - Proficiency in Python along with SQL. - Experience working with Databricks or similar big data platforms.
- 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.
- Proficiency in Python along with SQL. - Experience working with Databricks or similar big data platforms. - Ability to clearly communicate complex statistical concepts to non-technical stakeholders.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Aug 12, 2026 · 74 days ago
- Recorded sightings
- 303
- Last seen by us
- Oct 25, 2026
- Employer says posted
- May 11, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on fa-ewjt-saasfaprod1.fa.ocs.oraclecloud.com. The employer’s form will show what is required.
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Job description
This role is heavily focused on econometric modeling, time series analysis, and causal inference, with applications in forecasting, pricing, and customer behavior analytics. The ideal candidate brings deep expertise in statistical modeling and is comfortable working with large-scale data environments.
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.
Must-Have Qualifications
- Strong foundation in econometrics and time series analysis (this is critical for the role).
- Hands-on experience with:
- Time series models (ARIMA, SARIMA, VAR, forecasting techniques)
- Econometric methods (WLS, regression diagnostics, panel data models)
- Causal inference (A/B testing, quasi-experimental methods)
- Bayesian statistics and probabilistic modeling
- Markov chains or stochastic modeling
- Proficiency in Python along with SQL.
- Experience working with Databricks or similar big data platforms.
- Ability to clearly communicate complex statistical concepts to non-technical stakeholders.
Secondary / Good-to-Have Skills (General Data Science)
- Experience with machine learning models (classification, regression, tree-based models, etc.)
- Familiarity with feature engineering, model validation, and performance tuning
- Exposure to ML pipelines and MLOps concepts
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Gurugram, Haryana, India
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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