Data Scientist - Knowledge Graph | Pune

Sr.Data Scientist,Python, AI ML

We are looking for a skilled Data Scientist to analyze complex datasets, develop predictive models, and generate actionable insights that support business decisions. The ideal candidate should have strong statistical, analytical, and programming skills, along with hands-on experience in machine learning.

Role Overview 

As a Data Scientist, you will work with business stakeholders, AI engineers, and domain experts to transform data into actionable insights and intelligent solutions. You will develop machine learning models, perform statistical analysis, and contribute to AI-driven products that create measurable business impact. 

Key Responsibilities 

Data Science & Machine Learning 

• Analyze structured and unstructured data to identify patterns, trends, and business opportunities.  
• Perform exploratory data analysis (EDA), feature engineering, and data preparation.  
• Develop, evaluate, and optimize machine learning models for prediction, classification, clustering, and forecasting.  
• Apply statistical techniques to solve business problems and validate model performance.  
• Design and execute experiments to improve model accuracy and business outcomes.  

 AI Solution Development 

• Collaborate with AI Engineers, Data Engineers, and domain experts to build AI-powered solutions.  
• Translate business requirements into scalable data science approaches.  
• Contribute to Generative AI and advanced analytics initiatives where applicable.  
• Document methodologies, model performance, and key findings.  

 Required Technical Skills 

• Strong programming skills in Python and SQL for data analysis, feature engineering, and machine learning.  
• Strong understanding of Statistics, Probability, Linear Algebra, and Calculus as applied to machine learning and data science.  
• Experience with Exploratory Data Analysis (EDA), data preprocessing, feature engineering, feature selection, and handling missing or imbalanced data.  
• Good understanding of Supervised, Unsupervised, and Ensemble Machine Learning algorithms, including their assumptions, strengths, limitations, and appropriate use cases.  
• Strong knowledge of Regression, Classification, Clustering, Time Series Forecasting, Dimensionality Reduction, Recommendation Systems, and Anomaly Detection techniques.  
• Experience with Model Evaluation, Cross-Validation, Hyperparameter Optimization, Bias-Variance Trade-off, Feature Importance, Explainable AI (XAI), and Performance Metrics.  
• Understanding of Statistical Inference, Hypothesis Testing, Probability Distributions, Sampling Techniques, Confidence Intervals, and A/B Testing.  
• Experience translating business problems into analytical approaches and developing scalable, data-driven solutions.  
• Working knowledge of Generative AI, Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG) is preferred. 

Preferred Qualifications 

• Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, Statistics, Mathematics, Engineering, or a related field.  
• 2–4 years of experience developing machine learning or data science solutions.  
• Experience working on end-to-end data science projects in a business environment.  

 Nice to Have 

• Exposure to Generative AI, LLMs, RAG, or Agentic AI.  
• Experience with Computer Vision or Natural Language Processing (NLP).  
• Familiarity with cloud-based AI platforms.  
• Knowledge of construction, engineering, manufacturing, or industrial domains.  
• Participation in hackathons, research, Kaggle competitions, or open-source projects.  

 Soft Skills 

Strong analytical and problem-solving skills, effective communication and collaboration, ownership mindset, adaptability, continuous learning, and a passion for innovation.

Hiring for Data Scientist / Senior Data Scientist

Exp : 4 - 12 yrs

Edu : BE/B.tech/MCA

Work Location : Pune

Notice Period : Immediate - 15 days

Skills :

4+ years of experience in data engineering, data science, or related domains.

Hands-on experience with SQL, Python, and distributed data systems.

Knowledge of machine learning techniques and statistical analysis.

Experience with cloud data platforms (Azure Data Factory, AWS Glue, GCP BigQuery).

Familiarity with DevOps practices and CI/CD for data pipelines.

Platforms & Operations Experience (Preferred)

- Experience working with Azure, AWS, or Google Cloud data tools.

Operational experience with data orchestration tools (Airflow, ADF, Glue).

Understanding of Kubernetes, Docker, or containerized environments.

Hands-on experience with data warehousing platforms (Snowflake, Redshift, BigQuery).

Experience in monitoring, logging, and alerting operations for data workflows.

We are looking for a talented and driven Data Scientist to join our growing Analytics team in India. In this role, you will work at the intersection of advanced machine learning, scalable MLOps infrastructure, and domain-specific healthcare analytics. You will collaborate closely with cross-functional teams to build, deploy, and maintain production-grade ML models that drive real-world impact in clinical trials and healthcare operations.

KEY RESPONSIBILITIES

End-to-End ML Development

•     Design, build, and optimize predictive models across the full ML lifecycle—from data ingestion to model serving.

•     Conduct rigorous Exploratory Data Analysis (EDA) to surface insights and drive feature engineering decisions.

•     Validate model performance using appropriate statistical techniques and domain knowledge.

MLOps & Production Deployment

•     Deploy, monitor, and maintain production-grade ML models using Databricks MLFlow endpoints and Unity Catalog.

•     Implement CI/CD pipelines for model versioning, experiment tracking, and automated retraining.

•     Ensure model reliability, observability, and performance in live production environments.

Language Models & LLM Applications

•     Apply transformer-based models (BERT, ClinicalBERT, Trial2Vec) for NLP tasks including classification, NER, and information extraction.

•     Build and maintain vector similarity search pipelines for semantic retrieval and recommendation use cases.

•     Fine-tune pre-trained models for domain-specific applications in clinical and healthcare contexts.

•     Support exploratory work around LLM integration and prompt engineering for internal tooling.

Domain-Driven Analytics

•     Apply advanced analytics within complex healthcare and clinical trial datasets—including patient records, trial protocols, and adverse event data.

•     Translate ambiguous business problems into structured analytical frameworks with measurable outcomes.

•     Partner with domain experts, product managers, and engineering teams to deliver data-driven solutions.

REQUIRED QUALIFICATIONS

Education

•     Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Bioinformatics, or a closely related field.

Experience

•     2–4 years of hands-on experience in a data science or machine learning role.

•     Demonstrable experience deploying ML models in production environments (not just prototyping).

Technical Skills

•     Strong proficiency in Python (pandas, NumPy, scikit-learn, PyTorch / TensorFlow).

•     Experience with Databricks, MLFlow (experiment tracking, model registry, endpoints), and Unity Catalog.

•     Hands-on experience with BERT-family models and Hugging Face Transformers library.

•     Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and embedding-based retrieval.

•     Solid understanding of SQL and working with large structured/unstructured datasets.

•     Exposure to cloud platforms (AWS / GCP / Azure) and distributed computing frameworks (Spark).

GOOD TO HAVE

•     Prior experience with clinical trial data standards (CDISC, CDASH, SDTM) or healthcare ontologies (SNOMED, ICD-10).

•     Familiarity with Trial2Vec or similar trial-to-vector embedding approaches.

•     Experience with LLM fine-tuning, RAG pipelines, or prompt engineering in a production setting.

•     Knowledge of regulatory and compliance considerations in healthcare AI (e.g., FDA guidelines, HIPAA).

•     Contributions to open-source ML projects or published research.

THIS ROLE IS NOT FOR YOU IF…

•     You have strong SQL/BI skills but limited hands-on ML modelling experience — or you’ve built models only in notebooks without ever deploying them to production.

•     Your LLM exposure is limited to API calls and prompt engineering — with no experience fine-tuning models, working with embeddings, or building vector search pipelines.

Description

We’re seeking a highly skilled, execution-focused Senior Data Scientist with a minimum of 5 years of experience. This role demands hands-on expertise in building, deploying, and optimizing machine learning models at scale, while working with big data technologies and modern cloud platforms. You will be responsible for driving data-driven solutions from experimentation to production, leveraging advanced tools and frameworks across Python, SQL, Spark, and AWS. The role requires strong technical depth, problem-solving ability, and ownership in delivering business impact through data science.

Responsibilities

• Design, build, and deploy scalable machine learning models into production systems.
• Develop advanced analytics and predictive models using Python, SQL, and popular ML/DL frameworks (Pandas, Scikit-learn, TensorFlow, PyTorch).
• Leverage Databricks, Apache Spark, and Hadoop for large-scale data processing and model training.
• Implement workflows and pipelines using Airflow and AWS EMR for automation and orchestration.
• Collaborate with engineering teams to integrate models into cloud-based applications on AWS.
• Optimize query performance, storage usage, and data pipelines for efficiency.
• Conduct end-to-end experiments, including data preprocessing, feature engineering, model training, validation, and deployment.
• Drive initiatives independently with high ownership and accountability.
• Stay up to date with industry best practices in machine learning, big data, and cloud-native deployments.

Requirements

• Minimum 5 years of experience in Data Science or Applied Machine Learning.
• Strong proficiency in Python, SQL, and ML libraries (Pandas, Scikit-learn, TensorFlow, PyTorch).
• Proven expertise in deploying ML models into production systems.
• Experience with big data platforms (Hadoop, Spark) and distributed data processing.
• Hands-on experience with Databricks, Airflow, and AWS EMR.
• Strong knowledge of AWS cloud services (S3, Lambda, SageMaker, EC2, etc.).
• Solid understanding of query optimization, storage systems, and data pipelines.
• Excellent problem-solving skills, with the ability to design scalable solutions.
• Strong communication and collaboration skills to work in cross-functional teams.

Benefits

• Best-in-class salary: We hire strong talent and compensate accordingly.
• Proximity Talks: Meet and learn from designers, engineers, product leaders, and AI practitioners.
• Continuous learning: Work with a world-class team and stay close to the latest in AI, engineering, and product development.
• High-impact work: Build AI-first systems and products used at scale by global clients.

About Us

Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media, and Entertainment companies in the world. We’re headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore.

Since 2019, Proximity has built high-impact, scalable products used by millions of users every day. Today, we are a global team of engineers, designers, product managers, and experts solving complex problems and building cutting-edge technology at scale.

🚀 We’re Hiring | Data Scientist 🧠📊

Ready to turn data into real-world intelligence? Join us and work on exciting AI/ML & data-driven solutions!

🔹 Experience: 8+ Years

🔹 Must-Have Skills:

🐍 Python | 🤖 Machine Learning | ☁️ Cloud | 🧠 NLP | 📊 Data Visualization

📍 Location: Pune

💼 Work Mode: Work from Office

If you're passionate about Data Science, AI & solving complex business problems, we’d love to hear from you!

📩 Interested? Kindly text

#Hiring #DataScientist #DataScience #MachineLearning #Python #NLP #AI #Cloud #DataVisualization #TechJobs #HiringNow

We are looking for a talented and driven Data Scientist to join our growing Analytics team in India. In this role, you will work at the intersection of advanced machine learning, scalable MLOps infrastructure, and domain-specific healthcare analytics. You will collaborate closely with cross-functional teams to build, deploy, and maintain production-grade ML models that drive real-world impact in clinical trials and healthcare operations.

KEY RESPONSIBILITIES

End-to-End ML Development

•     Design, build, and optimize predictive models across the full ML lifecycle—from data ingestion to model serving.

•     Conduct rigorous Exploratory Data Analysis (EDA) to surface insights and drive feature engineering decisions.

•     Validate model performance using appropriate statistical techniques and domain knowledge.

MLOps & Production Deployment

•     Deploy, monitor, and maintain production-grade ML models using Databricks MLFlow endpoints and Unity Catalog.

•     Implement CI/CD pipelines for model versioning, experiment tracking, and automated retraining.

•     Ensure model reliability, observability, and performance in live production environments.

Language Models & LLM Applications

•     Apply transformer-based models (BERT, ClinicalBERT, Trial2Vec) for NLP tasks including classification, NER, and information extraction.

•     Build and maintain vector similarity search pipelines for semantic retrieval and recommendation use cases.

•     Fine-tune pre-trained models for domain-specific applications in clinical and healthcare contexts.

•     Support exploratory work around LLM integration and prompt engineering for internal tooling.

Domain-Driven Analytics

•     Apply advanced analytics within complex healthcare and clinical trial datasets—including patient records, trial protocols, and adverse event data.

•     Translate ambiguous business problems into structured analytical frameworks with measurable outcomes.

•     Partner with domain experts, product managers, and engineering teams to deliver data-driven solutions.

REQUIRED QUALIFICATIONS

Education

•     Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Bioinformatics, or a closely related field.

Experience

•     2–4 years of hands-on experience in a data science or machine learning role.

•     Demonstrable experience deploying ML models in production environments (not just prototyping).

Technical Skills

•     Strong proficiency in Python (pandas, NumPy, scikit-learn, PyTorch / TensorFlow).

•     Experience with Databricks, MLFlow (experiment tracking, model registry, endpoints), and Unity Catalog.

•     Hands-on experience with BERT-family models and Hugging Face Transformers library.

•     Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and embedding-based retrieval.

•     Solid understanding of SQL and working with large structured/unstructured datasets.

•     Exposure to cloud platforms (AWS / GCP / Azure) and distributed computing frameworks (Spark).

GOOD TO HAVE

•     Prior experience with clinical trial data standards (CDISC, CDASH, SDTM) or healthcare ontologies (SNOMED, ICD-10).

•     Familiarity with Trial2Vec or similar trial-to-vector embedding approaches.

•     Experience with LLM fine-tuning, RAG pipelines, or prompt engineering in a production setting.

•     Knowledge of regulatory and compliance considerations in healthcare AI (e.g., FDA guidelines, HIPAA).

•     Contributions to open-source ML projects or published research.

THIS ROLE IS NOT FOR YOU IF…

•     You have strong SQL/BI skills but limited hands-on ML modelling experience — or you’ve built models only in notebooks without ever deploying them to production.

•     Your LLM exposure is limited to API calls and prompt engineering — with no experience fine-tuning models, working with embeddings, or building vector search pipelines.

Role & Responsibilities

Responsibilities

• Contribute to the development and optimization of enterprise-wide search systems and models.

• Design and implement algorithms to improve indexing, query relevance, and search accuracy.

• Support taxonomy, ontology, and metadata model creation for better search outcomes.

• Collaborate with business units (Loans, Insurance, Investments) to build AI-enabled search features.

• Conduct analysis of user behavior and system metrics to refine search performance.

• Work with engineers, product managers, and designers to deliver integrated search solutions.

• Develop production-grade ML systems for ranking, personalization, and recommendations.

• Participate in proof-of-concept initiatives with internal and external partners.

• Follow best practices in software engineering including CI/CD, testing, and monitoring.

• Keep abreast of emerging developments in AI/ML to apply them in practical solutions.

Ideal Candidate

Strong Data Scientist / AI Engineer / Machine Learning Engineer profiles.

Mandatory (Experience 1) – Must have minimum 5+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.

Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.

Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.

Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.

Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.

Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.

Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.

Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

Mandatory (Age) - Candidate's Age should be below 30 Years

Preferred (Experience 1) – Experience with MLFlow, Kubeflow, Airflow, Prefect, Feature Stores, Model Registry, or MLOps/LLMOps frameworks.

Preferred (Experience 2) – Experience working with Vector Databases, Spark, PySpark, distributed ML pipelines, large-scale data processing, or real-time ML systems..

Preferred (Experience 3) – Familiarity with Docker, Kubernetes, Azure, AWS, GCP, cloud-native AI deployments, and scalable ML architecture.

Preferred (Company) – Candidates from AI-first startups, Fintech, Banking, Lending, Fraud Analytics, Risk Analytics, Product Companies, SaaS organizations, or data-driven technology companies.

Kindly provide the following details while sending your CV: (Mandatory details)

1) Date of Birth

2) Current Location-

3) Current CTC-

4) Expected CTC-

5) Notice Period-

6) Ready to relocate to Pune?

Regards,

The Supreme Consultancy

Website- https://lnkd.in/eawfxfxU

AuxoAI is seeking a Senior Applied Scientist to design and deploy structured knowledge systems that enable reliable, schema-grounded AI and agent reasoning.

This role sits at the intersection of large language models, knowledge graphs, semantic architectures, and hybrid retrieval systems. The ideal candidate will build systems that transform unstructured data into structured knowledge representations, enforce semantic constraints, and enable hybrid symbolic–neural reasoning in production environments.

You will play a key role in designing scalable semantic infrastructures that support advanced AI use cases such as GraphRAG pipelines, structured extraction, and agent reasoning workflows.

You will work on problems where existing architectures may not be sufficient and will experiment with new approaches that combine machine learning, knowledge graphs, semantic constraints, and classical AI techniques to build reliable, production-grade systems.

Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)

Responsibilities:

• Design schema-guided information extraction systems using zero-shot and few-shot structured prompting, constrained decoding approaches such as JSON schema enforcement or grammar-based decoding, and function-calling or tool-driven extraction techniques.
• Develop recursive or multi-stage extraction pipelines capable of handling nested entities, hierarchical structures, and cross-document relationships.
• Build ontology-driven systems using frameworks such as LinkML, OWL, SHACL, or similar schema modeling tools, and implement knowledge representations using RDF triples or labeled property graphs.
• Design and optimize entity resolution algorithms using techniques such as blocking strategies, embedding similarity, and rule-based matching.
• Develop ontology alignment techniques and graph embedding models such as Node2Vec or TransE-style approaches where appropriate.
• Design hybrid retrieval architectures combining dense vector retrieval, sparse retrieval techniques, and graph traversal algorithms such as BFS, DFS, path ranking, and neighborhood expansion.
• Build validation systems that enforce schema conformance, detect semantic inconsistencies, and reduce hallucinated or invalid structured outputs.
• Integrate structured knowledge systems into GraphRAG pipelines, agent planning frameworks, and tool-selection workflows.
• Deliver production-grade semantic systems with clear targets for latency, scalability, reliability, and data integrity.

Requirements

• 5+ years of experience building production AI or machine learning systems.
• Strong experience designing and implementing knowledge graphs or ontology-driven architectures.
• Hands-on experience implementing structured extraction techniques, including grammar-constrained decoding, JSON schema enforcement, or AST-style parsing approaches.
• Experience building entity resolution systems beyond simple embedding similarity methods.
• Experience working with graph query languages such as SPARQL or Cypher and optimizing graph query performance.
• Familiarity with RDF, OWL, or property graph data models and semantic data architectures.
• Strong Python engineering skills, with emphasis on data validation, schema integrity, and system reliability.
• Experience designing hybrid symbolic and neural AI systems.

Nice to Have:

• Experience implementing graph algorithms such as PageRank, community detection, or shortest-path algorithms for reasoning chains.
• Experience building graph-enhanced retrieval systems such as GraphRAG.
• Experience designing compositional semantic extraction pipelines.
• Experience implementing reasoning engines or rule-based inference systems.
• Experience benchmarking and evaluating structural extraction accuracy and consistency.

Job Summary:

We are looking for a skilled Data Scientist with strong expertise in demand forecasting, predictive analytics, and emerging Generative AI technologies. The ideal candidate should have hands-on experience in machine learning, deep learning, NLP, and LLM-based solutions, along with proficiency in Python, SQL, Power BI, and advanced Excel. This role involves building scalable forecasting models and leveraging AI/GenAI to deliver actionable business insights.

Key Responsibilities:

• Develop and deploy demand forecasting models using machine learning and deep learning techniques.
• Analyze historical data to identify trends, seasonality, and demand patterns.
• Build predictive models to improve supply chain and inventory planning.
• Work with large datasets using Python and SQL for data extraction, transformation, and analysis.
• Design dashboards and reports using Power BI for business stakeholders.
• Utilize advanced Excel techniques (Pivot Tables, Power Query, formulas) for analysis and reporting.
• Build and integrate NLP-based solutions for text data analysis and insights.
• Develop and implement LLM-based applications using Generative AI frameworks.
• Design and deploy RAG (Retrieval-Augmented Generation) pipelines for intelligent data retrieval and response generation.
• Collaborate with cross-functional teams (operations, finance, product) to align forecasting and AI solutions.
• Continuously improve model accuracy and performance through experimentation and optimization.

Required Skills:

• Strong proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch).
• Solid understanding of machine learning & deep learning algorithms.
• Experience in demand forecasting / time-series analysis (ARIMA, Prophet, LSTM, etc.).
• Hands-on experience with NLP techniques and libraries (NLTK, SpaCy, Transformers).
• Experience working with LLMs and Generative AI frameworks (OpenAI, Hugging Face, LangChain, etc.).
• Strong understanding of RAG architectures and vector databases (FAISS, Pinecone, etc.).
• Advanced knowledge of SQL for data manipulation.
• Hands-on experience with Power BI for visualization and reporting.
• Expertise in advanced Excel (Power Query, dashboards, data modeling).
• Strong analytical and problem-solving skills. 

Preferred Qualifications:

• Experience in supply chain, logistics, or e-commerce forecasting.
• Knowledge of cloud platforms (AWS, Azure, or GCP).
• Familiarity with data pipelines and ETL processes.
• Understanding of business metrics and KPIs related to demand planning.