Data Scientist - Sr Consultant / Manager
Capgemini
Data Scientist - Sr Consultant / Manager
Job Description
Data Scientist - Sr Consultant / Manager
📋 Job Overview
The Data Scientist - Sr Consultant / Manager role at Capgemini Invent involves implementing AI-based solutions for the Intelligent Industry vertical, focusing on designing and developing ML and NLP models. The position requires taking ownership of data science projects from conceptualization to implementation, ensuring alignment with client needs, data security, and infrastructure. Professionals will collaborate with stakeholders, demonstrate domain expertise, and contribute to ML asset creation while fostering learning and training within the team.
📍 Location: Bangalore
💼 Experience Level: Experienced Professionals
🏢 Business Unit: INVENT
🎯 Key Responsibilities
- Implement Artificial Intelligence based solutions across various disciplines for the Intelligent Industry vertical
- Design and develop ML/NLP models as per requirements
- Work closely with Product Owner, Systems Architect, and key stakeholders from conceptualization to implementation
- Take ownership of client requirements, data usage, security & privacy needs, and infrastructure for development and implementation
- Execute data science projects independently to deliver business outcomes
- Demonstrate domain expertise, develop and execute program plans
- Proactively solicit feedback from stakeholders to identify improvement actions
- Collaborate on ML asset creation
- Learn and impart trainings to fellow data science professionals
✅ Required Qualifications
- Experience in predictive and prescriptive modeling using statistical and machine learning algorithms including Time Series, Regression, Trees, Ensembles, Neural-Nets (CNN, LSTM, Transformers)
- Knowledge of unsupervised learning techniques such as Market Basket Analysis, Collaborative Filtering, Dimensionality Reduction, SVD, and various clustering approaches (Hierarchical, Centroid-based, Density-based, Distribution-based, Graph-based like Spectral)
- Proficiency in NLP tasks including Information Extraction, Similarity Matching, Sentiment Analysis, Text Clustering, Semantic Analysis, Document Summarization, Context Mapping, Intent Classification, Word Embeddings, Vector Space Models
- Experience in model deployment including ML pipeline formation, data security, scrutiny checks, and ML-Ops for on-premises and cloud productionizing
- Ability to execute data science projects independently to deliver business outcomes
- Demonstrate domain expertise and develop/execute program plans
- Proactively solicit feedback from stakeholders to identify improvements
- Collaborate on ML asset creation
- Eager to learn and impart trainings to fellow data science professionals
⭐ Preferred Qualifications
- Experience with open-source OCR engines like Tesseract
- Speech recognition
- Computer Vision
- Face recognition
- Emotion detection
- Experience with NLP libraries like NLTK, Spacy, Stanford Core-NLP
- Usage of Transformers for NLP
- Experience with LLMs like ChatGPT, Llama
- Usage of RAGs with vector stores like LangChain & LangGraph
- Building Agentic AI applications
- Valuable certifications in latest technologies such as Generative AI
🛠️ Required Skills
- Programming Languages: Python, NumPy, SciPy, Pandas, Matplotlib, Seaborn
- Databases: RDBMS (MySQL, Oracle), NoSQL Stores (HBase, Cassandra)
- ML/DL Frameworks: Scikit-Learn, TensorFlow (Keras), PyTorch
- Big Data ML Frameworks: Spark (Spark-ML, GraphX), H2O
- Cloud: Azure, AWS, GCP
🎁 Benefits & Perks
- Flexible work arrangements including remote work and flexible hours to maintain work-life balance
- Career growth programs and diverse professional opportunities
- Valuable certifications in latest technologies such as Generative AI
Locations
- Bangalore, India
Salary
Estimated Salary Rangemedium confidence
2,500,000 - 4,200,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Programming Languages: Python, NumPy, SciPy, Pandas, Matplotlib, Seabornintermediate
- Databases: RDBMS (MySQL, Oracle), NoSQL Stores (HBase, Cassandra)intermediate
- ML/DL Frameworks: Scikit-Learn, TensorFlow (Keras), PyTorchintermediate
- Big Data ML Frameworks: Spark (Spark-ML, GraphX), H2Ointermediate
- Cloud: Azure, AWS, GCPintermediate
Required Qualifications
- Experience in predictive and prescriptive modeling using statistical and machine learning algorithms including Time Series, Regression, Trees, Ensembles, Neural-Nets (CNN, LSTM, Transformers) (experience)
- Knowledge of unsupervised learning techniques such as Market Basket Analysis, Collaborative Filtering, Dimensionality Reduction, SVD, and various clustering approaches (Hierarchical, Centroid-based, Density-based, Distribution-based, Graph-based like Spectral) (experience)
- Proficiency in NLP tasks including Information Extraction, Similarity Matching, Sentiment Analysis, Text Clustering, Semantic Analysis, Document Summarization, Context Mapping, Intent Classification, Word Embeddings, Vector Space Models (experience)
- Experience in model deployment including ML pipeline formation, data security, scrutiny checks, and ML-Ops for on-premises and cloud productionizing (experience)
- Ability to execute data science projects independently to deliver business outcomes (experience)
- Demonstrate domain expertise and develop/execute program plans (experience)
- Proactively solicit feedback from stakeholders to identify improvements (experience)
- Collaborate on ML asset creation (experience)
- Eager to learn and impart trainings to fellow data science professionals (experience)
Preferred Qualifications
- Experience with open-source OCR engines like Tesseract (experience)
- Speech recognition (experience)
- Computer Vision (experience)
- Face recognition (experience)
- Emotion detection (experience)
- Experience with NLP libraries like NLTK, Spacy, Stanford Core-NLP (experience)
- Usage of Transformers for NLP (experience)
- Experience with LLMs like ChatGPT, Llama (experience)
- Usage of RAGs with vector stores like LangChain & LangGraph (experience)
- Building Agentic AI applications (experience)
- Valuable certifications in latest technologies such as Generative AI (experience)
Responsibilities
- Implement Artificial Intelligence based solutions across various disciplines for the Intelligent Industry vertical
- Design and develop ML/NLP models as per requirements
- Work closely with Product Owner, Systems Architect, and key stakeholders from conceptualization to implementation
- Take ownership of client requirements, data usage, security & privacy needs, and infrastructure for development and implementation
- Execute data science projects independently to deliver business outcomes
- Demonstrate domain expertise, develop and execute program plans
- Proactively solicit feedback from stakeholders to identify improvement actions
- Collaborate on ML asset creation
- Learn and impart trainings to fellow data science professionals
Benefits
- general: Flexible work arrangements including remote work and flexible hours to maintain work-life balance
- general: Career growth programs and diverse professional opportunities
- general: Valuable certifications in latest technologies such as Generative AI
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Data Scientist - Sr Consultant / Manager
Capgemini
Data Scientist - Sr Consultant / Manager
Job Description
Data Scientist - Sr Consultant / Manager
📋 Job Overview
The Data Scientist - Sr Consultant / Manager role at Capgemini Invent involves implementing AI-based solutions for the Intelligent Industry vertical, focusing on designing and developing ML and NLP models. The position requires taking ownership of data science projects from conceptualization to implementation, ensuring alignment with client needs, data security, and infrastructure. Professionals will collaborate with stakeholders, demonstrate domain expertise, and contribute to ML asset creation while fostering learning and training within the team.
📍 Location: Bangalore
💼 Experience Level: Experienced Professionals
🏢 Business Unit: INVENT
🎯 Key Responsibilities
- Implement Artificial Intelligence based solutions across various disciplines for the Intelligent Industry vertical
- Design and develop ML/NLP models as per requirements
- Work closely with Product Owner, Systems Architect, and key stakeholders from conceptualization to implementation
- Take ownership of client requirements, data usage, security & privacy needs, and infrastructure for development and implementation
- Execute data science projects independently to deliver business outcomes
- Demonstrate domain expertise, develop and execute program plans
- Proactively solicit feedback from stakeholders to identify improvement actions
- Collaborate on ML asset creation
- Learn and impart trainings to fellow data science professionals
✅ Required Qualifications
- Experience in predictive and prescriptive modeling using statistical and machine learning algorithms including Time Series, Regression, Trees, Ensembles, Neural-Nets (CNN, LSTM, Transformers)
- Knowledge of unsupervised learning techniques such as Market Basket Analysis, Collaborative Filtering, Dimensionality Reduction, SVD, and various clustering approaches (Hierarchical, Centroid-based, Density-based, Distribution-based, Graph-based like Spectral)
- Proficiency in NLP tasks including Information Extraction, Similarity Matching, Sentiment Analysis, Text Clustering, Semantic Analysis, Document Summarization, Context Mapping, Intent Classification, Word Embeddings, Vector Space Models
- Experience in model deployment including ML pipeline formation, data security, scrutiny checks, and ML-Ops for on-premises and cloud productionizing
- Ability to execute data science projects independently to deliver business outcomes
- Demonstrate domain expertise and develop/execute program plans
- Proactively solicit feedback from stakeholders to identify improvements
- Collaborate on ML asset creation
- Eager to learn and impart trainings to fellow data science professionals
⭐ Preferred Qualifications
- Experience with open-source OCR engines like Tesseract
- Speech recognition
- Computer Vision
- Face recognition
- Emotion detection
- Experience with NLP libraries like NLTK, Spacy, Stanford Core-NLP
- Usage of Transformers for NLP
- Experience with LLMs like ChatGPT, Llama
- Usage of RAGs with vector stores like LangChain & LangGraph
- Building Agentic AI applications
- Valuable certifications in latest technologies such as Generative AI
🛠️ Required Skills
- Programming Languages: Python, NumPy, SciPy, Pandas, Matplotlib, Seaborn
- Databases: RDBMS (MySQL, Oracle), NoSQL Stores (HBase, Cassandra)
- ML/DL Frameworks: Scikit-Learn, TensorFlow (Keras), PyTorch
- Big Data ML Frameworks: Spark (Spark-ML, GraphX), H2O
- Cloud: Azure, AWS, GCP
🎁 Benefits & Perks
- Flexible work arrangements including remote work and flexible hours to maintain work-life balance
- Career growth programs and diverse professional opportunities
- Valuable certifications in latest technologies such as Generative AI
Locations
- Bangalore, India
Salary
Estimated Salary Rangemedium confidence
2,500,000 - 4,200,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Programming Languages: Python, NumPy, SciPy, Pandas, Matplotlib, Seabornintermediate
- Databases: RDBMS (MySQL, Oracle), NoSQL Stores (HBase, Cassandra)intermediate
- ML/DL Frameworks: Scikit-Learn, TensorFlow (Keras), PyTorchintermediate
- Big Data ML Frameworks: Spark (Spark-ML, GraphX), H2Ointermediate
- Cloud: Azure, AWS, GCPintermediate
Required Qualifications
- Experience in predictive and prescriptive modeling using statistical and machine learning algorithms including Time Series, Regression, Trees, Ensembles, Neural-Nets (CNN, LSTM, Transformers) (experience)
- Knowledge of unsupervised learning techniques such as Market Basket Analysis, Collaborative Filtering, Dimensionality Reduction, SVD, and various clustering approaches (Hierarchical, Centroid-based, Density-based, Distribution-based, Graph-based like Spectral) (experience)
- Proficiency in NLP tasks including Information Extraction, Similarity Matching, Sentiment Analysis, Text Clustering, Semantic Analysis, Document Summarization, Context Mapping, Intent Classification, Word Embeddings, Vector Space Models (experience)
- Experience in model deployment including ML pipeline formation, data security, scrutiny checks, and ML-Ops for on-premises and cloud productionizing (experience)
- Ability to execute data science projects independently to deliver business outcomes (experience)
- Demonstrate domain expertise and develop/execute program plans (experience)
- Proactively solicit feedback from stakeholders to identify improvements (experience)
- Collaborate on ML asset creation (experience)
- Eager to learn and impart trainings to fellow data science professionals (experience)
Preferred Qualifications
- Experience with open-source OCR engines like Tesseract (experience)
- Speech recognition (experience)
- Computer Vision (experience)
- Face recognition (experience)
- Emotion detection (experience)
- Experience with NLP libraries like NLTK, Spacy, Stanford Core-NLP (experience)
- Usage of Transformers for NLP (experience)
- Experience with LLMs like ChatGPT, Llama (experience)
- Usage of RAGs with vector stores like LangChain & LangGraph (experience)
- Building Agentic AI applications (experience)
- Valuable certifications in latest technologies such as Generative AI (experience)
Responsibilities
- Implement Artificial Intelligence based solutions across various disciplines for the Intelligent Industry vertical
- Design and develop ML/NLP models as per requirements
- Work closely with Product Owner, Systems Architect, and key stakeholders from conceptualization to implementation
- Take ownership of client requirements, data usage, security & privacy needs, and infrastructure for development and implementation
- Execute data science projects independently to deliver business outcomes
- Demonstrate domain expertise, develop and execute program plans
- Proactively solicit feedback from stakeholders to identify improvement actions
- Collaborate on ML asset creation
- Learn and impart trainings to fellow data science professionals
Benefits
- general: Flexible work arrangements including remote work and flexible hours to maintain work-life balance
- general: Career growth programs and diverse professional opportunities
- general: Valuable certifications in latest technologies such as Generative AI
Tags & Categories
Answer 10 quick questions to check your fit for Data Scientist - Sr Consultant / Manager @ Capgemini.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs