Jr./Sr. Data Scientist

Location: Pune
Experience: 4–12 Years
Salary: As per experience and interview performance(The mentioned salary range is for reference and screening purposes only. Compensation will be determined based on the candidate’s relevant experience, skills, role fit, and applicable market standards.)
Notice Period: Immediate to 45 Days(596,597)
Work Mode: Pune / Local candidates preferred
Role Overview
We are looking for a Junior Data Scientist / Data Engineer with strong expertise in SQL, Python, Data Science, Cloud, and Spark. The role involves working with complex datasets, developing data pipelines and machine learning models, performing statistical analysis, and delivering actionable insights to business stakeholders.
The ideal candidate should have excellent communication skills and be comfortable working in a client-facing environment.
Must-Have Skills
Strong hands-on experience with SQL and Python
Strong understanding of Data Science and Machine Learning
Hands-on experience with Apache Spark / distributed data processing
Experience with at least one major cloud platform:
Microsoft Azure
AWS
Strong knowledge of:
Data preprocessing
Feature engineering
Model validation
Statistical analysis
Exploratory Data Analysis (EDA)
Experience working with large and complex datasets
Knowledge of data pipelines, ETL processes, and data quality
Excellent communication and stakeholder management skills
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field
Nice-to-Have Skills
Experience with Azure Data Factory, AWS Glue, or GCP BigQuery
Experience with Airflow, ADF, or other data orchestration tools
Knowledge of Tableau, Power BI, Matplotlib, or Seaborn
Experience with Snowflake, Redshift, BigQuery, or other data warehousing platforms
Knowledge of Hadoop
Experience with AWS SageMaker, Azure ML, or GCP AI/ML platforms
Understanding of A/B testing, experimental design, and hypothesis testing
Experience with Docker or Kubernetes
Knowledge of CI/CD and DevOps practices for data pipelines
Experience with monitoring, logging, and alerting for data workflows
Experience deploying and monitoring machine learning models in production
Familiarity with AI foundation models and their application in data science
Key Responsibilities
Design, build, and optimize scalable data pipelines and ETL processes
Develop and maintain data models, data marts, and analytical datasets
Analyze large datasets to identify trends, patterns, and business insights
Perform EDA, statistical analysis, and hypothesis testing
Develop, train, and validate predictive and classification models
Perform data preprocessing and feature engineering
Implement data quality checks and validation processes
Collaborate with data engineers to prepare and optimize datasets
Translate analytical findings into actionable business recommendations
Create reports and dashboards using data visualization techniques
Monitor and maintain models in production
Automate data workflows and ensure timely availability of data
Work with cloud platforms and distributed data systems
Communicate technical findings clearly to technical and non-technical stakeholders
Data Quality & Testing
Develop data validation and data quality test cases
Perform unit and integration testing for data pipelines
Monitor data accuracy, completeness, and consistency
Identify data anomalies and coordinate with engineering teams for resolution
Document test results and maintain testing records
Candidate Requirements
Experience: 4–8 years in Data Science, Data Engineering, or related areas
Relevant Experience: Minimum 3–5 years in relevant data engineering/data science work
Job Stability: Minimum 2 years with an organization is preferred
Notice Period: Immediate to 45 days
Location: Pune candidates preferred
Communication: Excellent communication skills are mandatory
Education: Bachelor’s/Master’s degree in CS, Data Science, Engineering, or related field
Interview Process
2 Technical Rounds → Client Round → HR Round
Skills: apache spark,eda,etl processes,azure data factory,data science,microsoft azure,adf,sql,python,redshift,distributed data processing,complex datasets,data pipelines,feature engineering,statistical analysis tools,model validation,data preprocessing,bigquery,aws,snowflake,stakeholder management,machine learning

Work arrangement
No