Senior

Data Scientist (m/f/d)

Pune, India · On-site

Job Description

Job Description: Data Scientists

The candidate should be a highly skilled Data Scientist with hands-on experience in building and deploying data-driven solutions. The ideal candidate should be comfortable working with large datasets, applying advanced statistical and machine learning techniques, and translating business problems into actionable insights.

Key Responsibilities:

Analyze large volumes of structured and unstructured data to extract meaningful insights.
Build, validate, and deploy machine learning models for predictive analytics and automation.
Design and implement machine learning pipelines for structured and unstructured data.
Work closely with business stakeholders and cross-functional teams including data engineers, & analysts to translate problems into data-driven solutions.
Build dashboards and data visualizations to communicate findings effectively.
Conduct testing, hypothesis validation, and experiment tracking.
Optimize model performance and ensure scalability and maintainability in production environments.
Document methodology, workflow, and results clearly for future reference and compliance.
Continuously monitor model performance and retrain based on data drift and feedback loops.

Required Skills & Tools:

Good To have:

Experience with NLP, GenAI/LLMs, or recommendation systems is a plus.
Familiarity with MLOps practices and tools (e.g., Kubeflow, Airflow) is a bonus.

Qualifications

Additional Information

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Your Task

The role is for a Data Scientist who will be responsible for building and deploying data-driven solutions. The ideal candidate should be comfortable working with large datasets, applying advanced statistical and machine learning techniques, and translating business problems into actionable insights.

Responsibilities

Analyze large volumes of structured and unstructured data to extract meaningful insights
Build, validate, and deploy machine learning models for predictive analytics and automation
Design and implement machine learning pipelines for structured and unstructured data
Work closely with business stakeholders and cross-functional teams including data engineers and analysts to translate problems into data-driven solutions
Build dashboards and data visualizations to communicate findings effectively
Conduct testing, hypothesis validation, and experiment tracking
Optimize model performance and ensure scalability and maintainability in production environments
Document methodology, workflow, and results clearly for future reference and compliance
Continuously monitor model performance and retrain based on data drift and feedback loops

Your Profile

We are looking for a highly skilled Data Scientist with expertise in machine learning, statistical analysis, and data engineering to build and deploy data-driven solutions while working with large datasets and cross-functional teams.

Must Have Skills

Experience in Python programming with libraries such as pandas, scikit-learn, NumPy, matplotlib, and seaborn
Knowledge of R programming language
Proficiency in SQL
Experience with supervised and unsupervised machine learning techniques
Experience with time series forecasting
Experience with clustering algorithms
Experience with Natural Language Processing (NLP)
Knowledge of statistical analysis including hypothesis testing, regression models, Bayesian inference, and multivariate analysis
Experience in data preprocessing, cleaning, and feature engineering
Experience handling large datasets
Knowledge of big data tools such as Spark, Hadoop, and Hive
Experience with model deployment using MLflow
Experience with Docker
Proficiency in data visualization tools including Power BI, Tableau, Plotly, Matplotlib, and Seaborn
Experience with SQL and NoSQL databases (MongoDB, Cassandra)
Experience with cloud-native databases (BigQuery, Redshift, Snowflake)
Experience with cloud platforms such as AWS (SageMaker, Redshift), GCP (Vertex AI, BigQuery), or Azure (ML Studio, Data Lake)
Proficiency in version control using Git, GitHub/GitLab
Experience working with Agile teams
Experience using collaboration tools like Jira, Confluence, and Slack

Nice to Have Skills

Experience with deep learning techniques
Experience with NLP, GenAI/LLMs, or recommendation systems
Experience with Kubernetes (for advanced roles)
Familiarity with MLOps practices and tools (e.g., Kubeflow, Airflow)

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