Data Scientist - R01572016

Lever, Inc.; Pune District; On-site; INR 1,500,000 - 2,600,000; Full time

Job summary

Lever, Inc. is seeking a Data Scientist in Pune with 4+ years of hands-on experience in advanced data science, statistics, and ML. You will design models, build predictive algorithms, and translate data insights into business actions.

You will work with Python, PySpark, SAS, SPSS, and various ML frameworks, deploying models to production and validating data quality. Strong communication with stakeholders is essential.

Qualifications

• 4+ years hands-on data science experience with statistical analysis and ML.
• Proficient in Python and PySpark for data manipulation and modeling.
• Extensive SAS and SPSS experience for statistical analysis.
• Experience with probabilistic graph models for complex data.
• Strong time series forecasting skills: exponential smoothing, ARIMA, ARIMAX.
• Knowledge of ML frameworks: TensorFlow, PyTorch, scikit-learn, CNTK, Keras, MXNet.
• Familiar with distance metrics: Hamming, Euclidean, Manhattan.
• Proficient with R and R Studio for statistics and visualization.

Responsibilities

• Design and implement statistical models to deliver actionable insights.
• Develop and optimize ML algorithms for classification, prediction, and graphs.
• Conduct statistical analyses using SAS, SPSS, and R Studio.
• Build, train, and deploy scalable models with major ML frameworks.
• Apply time series methods to forecast trends and outcomes.
• Streamline model deployment and lifecycle in production environments.
• Implement data quality checks with Great Expectations and Evidently AI.
• Present findings to stakeholders with clear, actionable recommendations.

Skills

Hypothesis testing (T-Test, Z-Test)

Regression analysis (linear & logistic

Python

PySpark

SAS

SPSS

Probabilistic graph models

Time series forecasting

Classification (DT, SVM)

ML frameworks (TF, PyTorch, scikit-lea

Education

Bachelor's degree in CS/Statistics/Math/Data Science

DS/ML certification (e.g., Azure ML, TensorFlow)

Job description

Data Scientist

Job requirements

Experience Range: With at least 4 years of hands‑on experience in advanced data science, including statistical analysis and machine learning, and up to 6 years in similar roles

Key Responsibilities

• Design and implement robust statistical models using advanced hypothesis testing, regression, and forecasting techniques to deliver actionable business insights
• Develop and optimize machine learning algorithms for classification, prediction, and probabilistic graph models utilizing Python, PySpark, and R
• Conduct comprehensive statistical analysis with SAS, SPSS, and R Studio to support data-driven decision-making
• Build, train, and deploy scalable models using ML frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, and MXNet
• Apply advanced time series forecasting methods, including exponential smoothing, ARIMA, and ARIMAX, to analyze trends and predict outcomes
• Streamline model deployment and lifecycle management in production environments using KubeFlow and BentoML
• Implement and validate data quality checks with Great Expectations and Evidently AI to ensure dataset integrity
• Present complex data findings to stakeholders, translating insights into actionable recommendations that drive business outcomes

Required Skills

• Advanced application of hypothesis testing methodologies, including T-Test and Z-Test
• Expert-level regression analysis (linear and logistic) for predictive modeling
• Proficient programming in Python and PySpark for data manipulation and model development
• Extensive experience with statistical analysis using SAS and SPSS
• Hands‑on expertise in probabilistic graph models for complex data relationships
• Mastery of time series forecasting techniques (exponential smoothing, ARIMA, ARIMAX)
• Implementation of classification algorithms such as decision trees and support vector machines (SVM)
• Deep familiarity with ML frameworks: TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet
• Calculation and application of distance metrics (Hamming, Euclidean, Manhattan)
• Skilled in R and R Studio for statistical analysis and visualization

Preferred Skills

• Practical experience with Great Expectations and Evidently AI for advanced data validation
• Proficiency in cloud-based model deployment tools such as KubeFlow and BentoML
• Background in large-scale data processing and distributed computing environments
• Expertise in feature engineering and model interpretability techniques
• Familiarity with cloud-based data science platforms such as AWS SageMaker, Azure ML, or Google Cloud AI Platform

Desired Qualifications

• Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related discipline
• Certification in Data Science or Machine Learning from a recognized institution, such as Microsoft Certified: Azure Data Scientist Associate or TensorFlow Developer Certificate