Data Scientist - R01572015

Lever, Inc.; Pune District; On-site; INR 1,500,000 - 2,800,000; Full time

Job summary

Lever, Inc. is seeking a Data Scientist with 4–6 years of hands-on data science experience to design statistical models, build ML algorithms, and deploy scalable solutions in a production environment.

The role requires strong Python, PySpark, and R skills, plus experience with SAS/SPSS for rigorous analysis. You will work on time series forecasting, probabilistic graph models, and model validation using Great Expectations and Evidently AI.

Qualifications

• 4+ years hands-on data science experience with statistical analysis and machine learning.
• Proficient in Python, PySpark, and R for data manipulation and modeling.
• Experience with SAS and SPSS for statistical analysis.
• Hands-on expertise in probabilistic graph models for complex data relationships.
• Strong time series forecasting knowledge (e.g., exponential smoothing, ARIMA, ARIMAX).
• Experience deploying models using ML frameworks (TensorFlow, PyTorch, Scikit-Learn).
• Familiar with data quality checks and validation tools (Great Expectations, Evidently AI).
• Ability to present findings to stakeholders and translate insights into business actions.

Responsibilities

• Design and implement robust statistical models to deliver actionable business insights.
• Develop and optimize ML algorithms for classification, prediction, and probabilistic graphs using Python, PySpark, and R.
• Conduct statistical analysis with SAS, SPSS, and R Studio to support decisions.
• Build, train, and deploy scalable models using TensorFlow, PyTorch, Scikit-Learn, CNTK, Keras, MXNet.
• Apply time series forecasting methods to analyze trends and predict outcomes.
• Oversee model deployment and lifecycle management in production with KubeFlow and BentoML.
• Implement data quality checks with Great Expectations and Evidently AI to ensure data integrity.
• Present complex findings to stakeholders and translate insights into recommendations.

Skills

Python

PySpark

R

SAS

SPSS

Statistics

Machine Learning

Hypothesis Testing

Time Series

Graph Models

ML Frameworks

Distance Metrics

R Studio

Education

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

DS/ML Certification

Tools

TensorFlow

PyTorch

Scikit-Learn

CNTK

Keras

MXNet

KubeFlow

BentoML

Great Expectations

Evidently AI

AWS SageMaker

Azure ML

Google Cloud AI Platform

SAS

SPSS

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