Senior Data Specialist - R01571898

Lever, Inc.; Pune District; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Lever, Inc. in Pune, India seeks a Senior Data Specialist with 5–8 years of hands-on experience in advanced data science, including statistical analysis and machine learning. You will design, validate, and deploy statistical models, perform rigorous analyses, and communicate insights to stakeholders.

Proficiency in Python, PySpark, and ML frameworks is required, with responsibility for end-to-end analytics and scalable workflows. Immediate joiner preferred.

Qualifications

• 5+ years of hands-on data science experience including statistical analysis and ML
• Experience with hypothesis testing, regression, and classification techniques
• Proficiency in Python and PySpark for data manipulation and modeling
• Hands-on use of SAS or SPSS for statistical computing
• Knowledge of probabilistic graph models and data validation frameworks
• Familiarity with time series forecasting (ARIMA/ETS) and model deployment workflows
• Ability to translate business needs into analytical solutions and communicate results clearly

Responsibilities

• Design and implement advanced statistical models to drive business outcomes
• Conduct rigorous statistical analyses using t-tests, z-tests, and probabilistic models
• Build, train, and deploy predictive models with TensorFlow, PyTorch, and scikit-learn
• Prepare data cleaning, transformation and exploratory analysis using Python, PySpark and R
• Apply time series forecasts (Exponential smoothing, ARIMA, ARIMAX) to inform decisions
• Develop and maintain data validation and monitoring pipelines (Great Expectations)
• Collaborate with cross-functional teams to translate requirements into solutions
• Automate ML workflows to improve deployment efficiency and scalability

Skills

Hypothesis testing

Advanced regression

Python

PySpark

R for stats

Time series forecasting

ML deployment

Model monitoring

Communicating insights

Education

Bachelor's degree in CS/Stats/Data Science

Data Science/ML certification

Tools

TensorFlow

PyTorch

Sci-Kit Learn

SAS

SPSS

Great Expectations

BentoML

KubeFlow

R

Job description

Senior Data Specialist

Job requirements

Experience Range

With at least 5 years of hands‑on experience in advanced data science, including statistical analysis and machine learning, and up to 8 years in related roles

Key Responsibilities

• Design and implement advanced statistical models, including hypothesis testing, regression analysis, and classification algorithms, to drive business outcomes
• Conduct rigorous statistical analysis using t-tests, z-tests, and probabilistic graph models to extract actionable insights from large datasets
• Build, train, and deploy predictive models for forecasting and classification tasks using machine learning frameworks such as TensorFlow, PyTorch, and Sci-Kit Learn
• Perform data cleaning, transformation, and exploratory analysis utilizing Python, PySpark, R, and statistical tools like SAS or SPSS
• Apply time series forecasting methods, including exponential smoothing, ARIMA, and ARIMAX, to predict trends and inform strategic decisions
• Develop and maintain data validation and monitoring pipelines to ensure data quality and model performance
• Collaborate with cross-functional teams to translate business requirements into analytical solutions and communicate findings effectively
• Automate machine learning workflows to streamline deployment and enhance scalability

Required Skills

• Expertise in hypothesis testing (t-test, z-test)
• Advanced regression analysis (linear and logistic)
• Programming proficiency in Python and PySpark
• Hands‑on experience with SAS or SPSS for statistical computing
• Knowledge of probabilistic graph models
• Experience with data validation frameworks such as Great Expectations
• Time series forecasting techniques (exponential smoothing, ARIMA, ARIMAX)
• Familiarity with classification algorithms (decision trees, SVM)
• Experience with machine learning frameworks (TensorFlow, PyTorch, Sci-Kit Learn)
• Proficiency in R for statistical modeling

Preferred Skills

• Experience with distance metrics (Hamming, Euclidean, Manhattan)
• Expertise in model monitoring tools beyond Great Expectations, such as Evidently AI
• Experience in deploying models using BentoML
• Familiarity with orchestration tools for ML workflows, such as KubeFlow
• Background in designing scalable machine learning pipelines

Desired Qualifications

• Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related discipline
• Certification in Data Science, Machine Learning, or Advanced Analytics (e.g., Microsoft Certified: Azure Data Scientist Associate, SAS Certified Data Scientist)
• Certification in Python or R programming (e.g., PCEP, PCAP, R Programming Certification)

Additional Information

Immediate joiner required