T-Systems ICT India

Enterprise IT services, cloud and security

Data Scientist

Data ScienceConfirmed live in the last 24 hours

Full-timePune, Maharashtra, IndiaNo salary listedHybrid

About the Job

Requirements

Hands-on experience building and deploying data-driven solutions.
Experience working with large datasets and applying statistical and machine learning techniques to translate business problems into actionable insights.
Programming skills in Python and its pandas, scikit-learn, NumPy, matplotlib, and seaborn libraries; R; and SQL.
Knowledge of supervised and unsupervised learning, time-series forecasting, clustering, and natural language processing.
Knowledge of hypothesis testing, regression models, Bayesian inference, and multivariate analysis.
Experience with data preprocessing, cleaning, feature engineering, and handling large datasets.
Experience with Spark, Hadoop, and Hive.
Experience with MLflow and Docker; Kubernetes is noted for advanced roles.
Skills in Power BI, Tableau, Plotly, Matplotlib, and Seaborn.
Knowledge of SQL and NoSQL databases, including MongoDB and Cassandra, and cloud-native databases such as BigQuery, Redshift, and Snowflake.
Experience with AWS services SageMaker and Redshift; GCP services Vertex AI and BigQuery; and Azure ML Studio and Data Lake.
Experience with Git and GitHub or GitLab.
Experience working with Agile teams and using tools such as Jira, Confluence, and Slack.

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 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.
Conduct testing, hypothesis validation, and experiment tracking.
Optimize model performance and ensure scalability and maintainability in production environments.
Document methodology, workflow, and results for future reference and compliance.
Monitor model performance and retrain models based on data drift and feedback loops.

Desired Qualifications

Deep learning is optional.
Experience with natural language processing, generative AI or large language models, or recommendation systems is a plus.
Familiarity with MLOps practices and tools such as Kubeflow or Airflow is a bonus.

Job Description

Job Description: Data Scientists

The candidate should be 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:

Category

Skills & Tools

Programming

Python (pandas, scikit-learn, NumPy, matplotlib, seaborn), R, SQL.

Machine Learning

Supervised/unsupervised learning, time series forecasting, clustering, NLP, deep learning (optional).

Statistical Analysis

Hypothesis testing, regression models, Bayesian inference, multivariate analysis.

Data Engineering

Data preprocessing, cleaning, feature engineering, large dataset handling.

Big Data Tools

Spark, Hadoop, & Hive.

Model Deployment

MLflow, Docker, Kubernetes (for advanced roles).

Visualization

Power BI, Tableau, Plotly, Matplotlib, Seaborn.

Databases

SQL, NoSQL (MongoDB, Cassandra), cloud-native databases (BigQuery, Redshift, Snowflake).

Cloud Platforms

AWS (SageMaker, Redshift), GCP (Vertex AI, BigQuery), Azure (ML Studio, Data Lake).

Version Control

Git, GitHub/GitLab.

Collaboration

Experience working with Agile teams, using tools like Jira, Confluence, Slack.

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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About the Company

T-Systems ICT India

Enterprise IT services, cloud and security

T-Systems ICT India provides IT services as the Deutsche Telekom IT arm, helping European and global enterprises with digital transformation. Its offerings include cloud infrastructure management, cybersecurity, and outsourced IT services, delivered through partnerships with cloud providers (Microsoft, AWS, Google) and a focus on sovereign cloud solutions that keep data within Europe. The company operates as a multi-cloud service provider with in-house data centers and specialist collaborations (e.g., NVIDIA) to build an industrial AI cloud in Europe. Differences from competitors come from its emphasis on European data sovereignty, a long track record with industrial clients, and integrated telecom-IT heritage that blends networking with IT operations. Its goal is to safeguard Europe’s digital future by delivering trusted, compliant cloud and AI capabilities that offer a European alternative to US-based hyperscalers.

Company size: 10,001+
Company stage: Not listed
Total funding: Not listed
Headquarters: Frankfurt, Germany
Founded: 2000

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