ABOUT THE ROLE

You are a seasoned Data Scientist, passionate about building robust, real-time machine learning solutions to combat financial crime. Working within the Risk & Fraud Team, you will leverage advanced statistical modeling and machine learning to detect, prevent, and adapt to evolving fraud threats. You thrive on solving complex problems with highly imbalanced data and delivering tangible risk reduction impact in a fast-paced environment.

You strongly believe in agile principles and use them to deliver value incrementally. You are eager to learn about new methodologies and practices and apply them directly in your work.

As a Senior Data Scientist you’ll be:

• Model Development & Risk Mitigation: Design, develop, and implement advanced ML/Statistical models to predict and prevent various fraud typologies. Focus on driving impact by optimising costs and reducing risk using ML/Stats models.
• Specialised Data Handling: Employ advanced techniques to manage and model highly imbalanced, large datasets characteristic of the fraud domain.
• Adaptive Systems: Build and maintain models that can quickly adapt to new and evolving fraud typologies and emerging threats.
• Real-Time MLOps: Develop, optimise, and deploy ML models for real-time/low-latency inference in production settings.
• Data & Feature Engineering: Utilize, enrich, and contribute to the feature store ecosystem, ensuring high-quality, scalable features for risk models.
• Performance Monitoring: Implement and maintain robust drift monitoring and model performance tracking to ensure deployed models remain effective and stable.
• Collaboration: Work closely with ML Engineers to productionize models leveraging AWS/GCP tech stack, and collaborate with Business and Product teams to understand requirements and solutionise data products.
• Exploration: Identify creative solutions in order to build relevant training data sets and explore the value of new data structures like knowledge graphs for relational fraud detection.

WHAT ARE WE LOOKING FOR

• You have 6+ years of experience in Software Development or Machine Learning, with a strong emphasis on practical model development and deployment.
• You are Strong in Python and have expert knowledge with Machine Learning tools/libraries (e.g., scikit-learn, statmodels, TensorFlow, Keras, or PyTorch).
• You have experience with big-data technologies such as Spark, SparkML, Hadoop etc. and have handled large data in a distributed processing environment. AWS, GCP, or Azure (anyone) cloud knowledge is preferred.
• You are proficient in ML training, optimising, feature selection and engineering, hyperparameter tuning and have knowledge about trade-offs in using different algorithms.
• You have demonstrated experience in developing and deploying a variety of ML-algorithms (e.g., logistic regressions, boosted trees, neural networks) that work in real-time settings.
• You have a good working knowledge with basic data table operations (SQL etc.), and data transform in the warehouse (dbt etc.).
• You are comfortable with ambiguity and are a self-starter—you take initiative in spotting opportunities and finding ways to solve challenges with data.
• Familiarity with Financial Services and Fintech space is preferred.
• You will be helping optimise all aspects of our sales funnel including finding ways to increase lead quality, reduce our cost of acquisition, optimise lead allocation, and improve the likelihood of successful lending outcomes for our members

Highly Desirable Skills:

• Exposure to Cost-Sensitive Learning techniques, where the economic impact of prediction errors is a key optimization factor.
• A decent idea and practical exposure to MLOps principles (e.g., model versioning, continuous integration/deployment for ML).
• Experience with Drift monitoring tools and frameworks.
• Exposure to Knowledge Graphs or graph database applications.

• Competitive Compensation -  competitive salary and share options
• Time Off – Generous annual leave on top of bank holidays.
• Parental Leave – Paid maternity, paternity, and adoption leave to support your family journey.
• Sabbatical – Extended unpaid and paid leave options after completing milestone years with Tide.
• Health Insurance – Private family insurance with additional OPD coverage and top-up options.
• Life & Accident Cover – Comprehensive accidental and life insurance protection.
• Mental Wellbeing – Access to therapy sessions, courses, meditations, and workshops.
• Volunteering & Development Days – Paid days annually for volunteering or personal growth.
• Learning & Development – Annual budget for books, courses, coaching, and more.
• WOO (Work Outside the Office) – Work from abroad for up to 90 days annually.
• Home Office Setup – Contribution towards setting up your home office
• Laptop Ownership – Keep your old laptop and get a new one when it’s time for a replacement.
• Snacks & Meals – Office perks with snacks, coffee, tea, and lunch (location dependent).

TIDEAN WAYS OF WORKING

At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. 

While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.

ABOUT THE ROLE

You are a seasoned Data Scientist, passionate about building robust, real-time machine learning solutions to combat financial crime. Working within the Risk & Fraud Team, you will leverage advanced statistical modeling and machine learning to detect, prevent, and adapt to evolving fraud threats. You thrive on solving complex problems with highly imbalanced data and delivering tangible risk reduction impact in a fast-paced environment.

You strongly believe in agile principles and use them to deliver value incrementally. You are eager to learn about new methodologies and practices and apply them directly in your work.

As a Senior Data Scientist you’ll be:

• Model Development & Risk Mitigation: Design, develop, and implement advanced ML/Statistical models to predict and prevent various fraud typologies. Focus on driving impact by optimising costs and reducing risk using ML/Stats models.
• Specialised Data Handling: Employ advanced techniques to manage and model highly imbalanced, large datasets characteristic of the fraud domain.
• Adaptive Systems: Build and maintain models that can quickly adapt to new and evolving fraud typologies and emerging threats.
• Real-Time MLOps: Develop, optimise, and deploy ML models for real-time/low-latency inference in production settings.
• Data & Feature Engineering: Utilize, enrich, and contribute to the feature store ecosystem, ensuring high-quality, scalable features for risk models.
• Performance Monitoring: Implement and maintain robust drift monitoring and model performance tracking to ensure deployed models remain effective and stable.
• Collaboration: Work closely with ML Engineers to productionize models leveraging AWS/GCP tech stack, and collaborate with Business and Product teams to understand requirements and solutionise data products.
• Exploration: Identify creative solutions in order to build relevant training data sets and explore the value of new data structures like knowledge graphs for relational fraud detection.

WHAT ARE WE LOOKING FOR

• You have 6+ years of experience in Software Development or Machine Learning, with a strong emphasis on practical model development and deployment.
• You are Strong in Python and have expert knowledge with Machine Learning tools/libraries (e.g., scikit-learn, statmodels, TensorFlow, Keras, or PyTorch).
• You have experience with big-data technologies such as Spark, SparkML, Hadoop etc. and have handled large data in a distributed processing environment. AWS, GCP, or Azure (anyone) cloud knowledge is preferred.
• You are proficient in ML training, optimising, feature selection and engineering, hyperparameter tuning and have knowledge about trade-offs in using different algorithms.
• You have demonstrated experience in developing and deploying a variety of ML-algorithms (e.g., logistic regressions, boosted trees, neural networks) that work in real-time settings.
• You have a good working knowledge with basic data table operations (SQL etc.), and data transform in the warehouse (dbt etc.).
• You are comfortable with ambiguity and are a self-starter—you take initiative in spotting opportunities and finding ways to solve challenges with data.
• Familiarity with Financial Services and Fintech space is preferred.
• You will be helping optimise all aspects of our sales funnel including finding ways to increase lead quality, reduce our cost of acquisition, optimise lead allocation, and improve the likelihood of successful lending outcomes for our members

Highly Desirable Skills:

• Exposure to Cost-Sensitive Learning techniques, where the economic impact of prediction errors is a key optimization factor.
• A decent idea and practical exposure to MLOps principles (e.g., model versioning, continuous integration/deployment for ML).
• Experience with Drift monitoring tools and frameworks.
• Exposure to Knowledge Graphs or graph database applications.

• Competitive Compensation -  competitive salary and share options
• Time Off – Generous annual leave on top of bank holidays.
• Parental Leave – Paid maternity, paternity, and adoption leave to support your family journey.
• Sabbatical – Extended unpaid and paid leave options after completing milestone years with Tide.
• Health Insurance – Private family insurance with additional OPD coverage and top-up options.
• Life & Accident Cover – Comprehensive accidental and life insurance protection.
• Mental Wellbeing – Access to therapy sessions, courses, meditations, and workshops.
• Volunteering & Development Days – Paid days annually for volunteering or personal growth.
• Learning & Development – Annual budget for books, courses, coaching, and more.
• WOO (Work Outside the Office) – Work from abroad for up to 90 days annually.
• Home Office Setup – Contribution towards setting up your home office
• Laptop Ownership – Keep your old laptop and get a new one when it’s time for a replacement.
• Snacks & Meals – Office perks with snacks, coffee, tea, and lunch (location dependent).

TIDEAN WAYS OF WORKING

At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. 

While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.

About the role

We are seeking a Senior Machine Learning Engineer in the Hyderabad area to design, build, and scale machine learning systems that power personalized and data-driven experiences across our digital entertainment ecosystem — including paid VOD streaming, Manga reading, Merchandising, Mobile Gaming, and Music Video platforms. The role will be reporting to the Manager of Machine Learning.

You will work at the intersection of user behavior, content intelligence, and product engagement, building models and systems that both enhance user experience (e.g., personalization, discovery, lifecycle optimization) and generate actionable business insights and services for internal stakeholders. As a senior individual contributor, you will own high-impact initiatives end-to-end and play a key role in shaping the technical direction of ML systems across products.

Core Areas of Responsibility

• Design, develop, and deploy scalable machine learning models that enhance personalization, discovery, engagement, and monetization across multiple product verticals.
• Lead end-to-end ML projects from problem framing and data exploration to production deployment and monitoring.
• Build and optimize robust data pipelines and feature engineering workflows for large-scale behavioral and content data.
• Design and execute rigorous experimentation frameworks (e.g., A/B testing, offline evaluation) to measure model impact.
• Collaborate closely with Product, Engineering, Analytics, and business stakeholders to translate product goals into ML solutions.
• Improve system reliability, scalability, and performance of production ML services.
• Mentor junior engineers and contribute to raising the team’s technical standards and best practices.
• Contribute to the evolution of ML architecture, tooling, and MLOps practices across the organization.

About You

Required Qualifications

• 8+ years of experience building and deploying machine learning systems in production environments
• Strong foundation in machine learning algorithms, statistics, and model evaluation techniques
• Experience working with large-scale user behavior or content datasets
• Proficiency in Python and common ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, xgboost)
• Experience with distributed data processing and data pipeline technologies
• Strong understanding of experimentation methodologies and performance measurement
• Ability to operate independently and drive ambiguous problems to impactful solutions

Preferred Qualifications

• Experience with recommendation systems, ranking models, personalization, or user lifecycle modeling
• Experience in subscription-based digital products, streaming media, gaming, or e-commerce platforms
• Familiarity with cloud infrastructure and production ML services
• Experience optimizing models for real-time or near real-time user-facing applications
  
  

What Success Looks Like

• ML systems you build measurably improve user engagement, retention, or monetization
• Models are reliable, scalable, and well-integrated into product workflows
• Stakeholders trust your technical judgment and rely on your work to inform product direction
• You elevate the team’s engineering rigor and contribute meaningfully to long-term ML platform evolution

About the Team

You will join a fast growing team of Data Scientists, Machine Learning Engineers, and AI Engineers, united by a passion for leveraging data and AI to create transformative solutions. Our team delivers both consumer-facing product features that enhance the streaming experience for millions of users and stakeholder-oriented solutions that empower internal teams with actionable insights. From building personalized recommendation systems to developing innovative tools like our stakeholder-facing chatbot, we combine cutting-edge machine learning, robust data pipelines, and advanced AI to drive impact across the organization. Collaboration, creativity, and a commitment to excellence define our team’s culture as we work together to push the boundaries of what’s possible in streaming and data-driven decision-making.

Lookout, Inc. is a globally recognized cybersecurity leader delivering advanced protection for the most vulnerable element of any enterprise security strategy — human error and manipulation. Cloud-native by design, the Lookout platform offers rapid, scalable deployment and simplified security operations, defending the frontline of human-centric attacks—the mobile device. Attackers now target the human element more than ever, with mobile devices providing the most direct path to their victims. Using social engineering techniques that exploit basic human instincts like trust, curiosity, and urgency, they deceive users into revealing sensitive credentials, allowing them to slip past legacy security solutions.

Lookout Endpoint Detection and Response (EDR) continuously monitors mobile endpoints for signs of human-centric attacks, as well as traditional malware, software vulnerabilities, and other anomalous activity. It uses advanced threat detection techniques, including artificial intelligence (AI) and behavioral analysis, to identify threats before they escalate across the enterprise. Learn more at www.lookout.com and follow us on the Lookout Blog, LinkedIn, and X.

Lookout’s backend system supports a massive volume of data and an increasingly high level of demand, from data ingestion to delivery to dynamic analysis. We’re looking for talented and motivated engineers to build core components and services, as well as to contribute to evolving the architecture. We’re a small team working on a very large, modern system with a user base of millions, so you’ll get to work on a cutting-edge product and service on a large scale. We’re responsible for building and maintaining several of the services powering the various Lookout applications..

What you’ll do:

• You will be part of a dynamic and technically diverse group of engineers, where you will get to contribute, influence, learn and grow top notch technical skill sets, while building key features for our customers.
• Own the full machine learning lifecycle, from initial research and design to production deployment, monitoring, and continuous retraining.
• Establish and implement robust frameworks to train, evaluate, stress-test, and monitor ML/AI systems, driving continuous improvement and preventing model drift.
• Address and navigate real-world scale and performance challenges, ensuring all ML/AI models and systems are efficient, robust, and maintain target quality/latency under production constraints.
• Set technical direction as a senior Individual Contributor (IC) and mentor junior engineers.
• Quality is the forefront of all we do, so you will assist with improving all forms of automated testing (unit, integration, functional etc).
• We believe in, and practice, end to end service ownership, so you will fully participate in the ownership of your services and components, including on-call duties.

What we’re looking for: 

• BS/MS in Computer Science or related field/degree with at least  5-8 years of  work experience.
• A proven track record of architecting and deploying practical, high-impact ML/AI systems over multiple years, translating complex models into robust, real-world solutions.
• Experience working cross-functionally with data engineers, platform engineers, and product stakeholders to bring ML/AI systems to life.
• Expert proficiency in Python and strong software engineering skills, including the ability to write reliable, production-grade code. In-depth experience with major ML/Deep Learning frameworks: PyTorch, TensorFlow, scikit-learn.
• Familiarity with modern AI/ML stacks like Hugging Face and LangChain.
• Deep expertise in a wide range of standard ML algorithms, including classification, clustering, regression, and deep learning models. 
• Hands-on experience with the LLM/RAG stack components: embeddings, knowledge graphs, vector databases, retrieval strategies, and prompt engineering. 
• Proven ability to measure and optimize model efficacy using statistical methods.
• Hands-on experience with production ML infrastructure, including feature stores, model management, training/serving pipelines (MLOps), and monitoring tools. 
• Up-to-date with new advances in NLP, LLMs and agent-frameworks.
• Strong grasp of software engineering fundamentals and algorithms.
• Experience with implementing secure, scalable API services.

Bonus Points:

• Practical experience applying advanced techniques to enhance model efficiency, including model distillation (creating smaller, faster student models) and model quantization (reducing memory footprint and latency).
• Experience with efficient Large Language Model (LLM) fine-tuning methods like LoRA and other PEFT techniques.
• Experience working with coding agents (Cursor, Copilot, Claude Code etc..)
• Experience with event streaming frameworks, technologies, patterns and architectures (particularly Kafka or similar)
• Professional programming experience with Scala and Golang
• Experience with serverless architectures on AWS, GCP.
• Experience with Kubernetes, container technology (Docker, ECS, EKS).

Lookout, Inc. is a globally recognized cybersecurity leader delivering advanced protection for the most vulnerable element of any enterprise security strategy — human error and manipulation. Cloud-native by design, the Lookout platform offers rapid, scalable deployment and simplified security operations, defending the frontline of human-centric attacks—the mobile device. Attackers now target the human element more than ever, with mobile devices providing the most direct path to their victims. Using social engineering techniques that exploit basic human instincts like trust, curiosity, and urgency, they deceive users into revealing sensitive credentials, allowing them to slip past legacy security solutions.

Lookout Endpoint Detection and Response (EDR) continuously monitors mobile endpoints for signs of human-centric attacks, as well as traditional malware, software vulnerabilities, and other anomalous activity. It uses advanced threat detection techniques, including artificial intelligence (AI) and behavioral analysis, to identify threats before they escalate across the enterprise. Learn more at www.lookout.com and follow us on the Lookout Blog, LinkedIn, and X.

Lookout’s backend system supports a massive volume of data and an increasingly high level of demand, from data ingestion to delivery to dynamic analysis. We’re looking for talented and motivated engineers to build core components and services, as well as to contribute to evolving the architecture. We’re a small team working on a very large, modern system with a user base of millions, so you’ll get to work on a cutting-edge product and service on a large scale. We’re responsible for building and maintaining several of the services powering the various Lookout applications..

What you’ll do:

• You will be part of a dynamic and technically diverse group of engineers, where you will get to contribute, influence, learn and grow top notch technical skill sets, while building key features for our customers.
• Own the full machine learning lifecycle, from initial research and design to production deployment, monitoring, and continuous retraining.
• Establish and implement robust frameworks to train, evaluate, stress-test, and monitor ML/AI systems, driving continuous improvement and preventing model drift.
• Address and navigate real-world scale and performance challenges, ensuring all ML/AI models and systems are efficient, robust, and maintain target quality/latency under production constraints.
• Set technical direction as a senior Individual Contributor (IC) and mentor junior engineers.
• Quality is the forefront of all we do, so you will assist with improving all forms of automated testing (unit, integration, functional etc).
• We believe in, and practice, end to end service ownership, so you will fully participate in the ownership of your services and components, including on-call duties.

What we’re looking for: 

• BS/MS in Computer Science or related field/degree with at least  5-8 years of  work experience.
• A proven track record of architecting and deploying practical, high-impact ML/AI systems over multiple years, translating complex models into robust, real-world solutions.
• Experience working cross-functionally with data engineers, platform engineers, and product stakeholders to bring ML/AI systems to life.
• Expert proficiency in Python and strong software engineering skills, including the ability to write reliable, production-grade code. In-depth experience with major ML/Deep Learning frameworks: PyTorch, TensorFlow, scikit-learn.
• Familiarity with modern AI/ML stacks like Hugging Face and LangChain.
• Deep expertise in a wide range of standard ML algorithms, including classification, clustering, regression, and deep learning models. 
• Hands-on experience with the LLM/RAG stack components: embeddings, knowledge graphs, vector databases, retrieval strategies, and prompt engineering. 
• Proven ability to measure and optimize model efficacy using statistical methods.
• Hands-on experience with production ML infrastructure, including feature stores, model management, training/serving pipelines (MLOps), and monitoring tools. 
• Up-to-date with new advances in NLP, LLMs and agent-frameworks.
• Strong grasp of software engineering fundamentals and algorithms.
• Experience with implementing secure, scalable API services.

Bonus Points:

• Practical experience applying advanced techniques to enhance model efficiency, including model distillation (creating smaller, faster student models) and model quantization (reducing memory footprint and latency).
• Experience with efficient Large Language Model (LLM) fine-tuning methods like LoRA and other PEFT techniques.
• Experience working with coding agents (Cursor, Copilot, Claude Code etc..)
• Experience with event streaming frameworks, technologies, patterns and architectures (particularly Kafka or similar)
• Professional programming experience with Scala and Golang
• Experience with serverless architectures on AWS, GCP.
• Experience with Kubernetes, container technology (Docker, ECS, EKS).

Senior Data Scientist

What You Can Expect from Us:

Here at NomiSo, we work hard to provide our team with the best opportunities to grow their careers.  You can expect to be a pioneer of ideas, a student of innovation, and a leader of thought. Innovation and thought leadership is at the center of everything we do, at all levels of the company. Let’s make your career great!

Position Overview: 

We are looking for an experienced Data Scientist with a strong academic background in Data Science and 8+ years of hands-on experience in Data science projects. The ideal candidate should be skilled in developing predictive models, performing data analysis, and applying advanced machine learning and AI techniques to solve complex business problems.

Roles and Responsibilities:

• Analyze large datasets to extract meaningful insights and patterns.
• Develop, implement, and optimize ML/AI models for predictive and prescriptive analytics
• Collaborate with engineering, product, and business teams to define and deliver data-driven solutions.
• Design and build data pipelines and perform data wrangling using Python, R, or SQL.
• Communicate analytical findings through clear data visualizations and storytelling techniques.
• Evaluate model performance and improve accuracy and efficiency.
• Work with cloud platforms (AWS, Azure, or GCP) to deploy and maintain ML/AI models in production.
• Ensure data quality, governance, and compliance with organizational standards.
  
  

Must Have Skill

• 8+ years of relevant experience in Data Science Machine Learning / AI projects.
• Proficiency in Python (pandas, NumPy, scikit-learn, TensorFlow, PyTorch) or R.
• Strong understanding of machine learning algorithms, statistical modeling, and data mining techniques.
• Experience with data visualization tools such as Power BI, Tableau, or Matplotlib/Seaborn.
• Strong SQL skills and experience with data pipelines (Airflow, Spark, etc.).
• Experience with cloud platforms such as AWS SageMaker, Azure ML, or Google AI Platform.
• Excellent analytical, problem-solving, and communication skills.
  
  

Good To Have:

• Experience with Deep Learning, NLP, or Time Series Analysis.
• Exposure to MLOps and CI/CD pipelines for model deployment.
• Certifications or project portfolios in Data Science or Machine Learning
• Experience in prompt engineering, context / RAG engineering, Agentic AI.
  
  

Qualification:

• Bachelor’s or Master’s or PhD degree in Data Science, or a related discipline.

Location:   Pune / Hyderabad 

Lead Data Scientist

What You Can Expect from Us:

Here at NomiSo, we work hard to provide our team with the best opportunities to grow their careers.  You can expect to be a pioneer of ideas, a student of innovation, and a leader of thought. Innovation and thought leadership is at the center of everything we do, at all levels of the company. Let’s make your career great!

Position Overview: 

We are looking for an experienced Data Scientist with a strong academic background in Data Science and 10+ years of hands-on experience in Data science projects. The ideal candidate should be skilled in developing predictive models, performing data analysis, and applying advanced machine learning and AI techniques to solve complex business problems.

Roles and Responsibilities:

• Analyze large datasets to extract meaningful insights and patterns.
• Develop, implement, and optimize ML/AI models for predictive and prescriptive analytics
• Collaborate with engineering, product, and business teams to define and deliver data-driven solutions.
• Design and build data pipelines and perform data wrangling using Python, R, or SQL.
• Communicate analytical findings through clear data visualizations and storytelling techniques.
• Evaluate model performance and improve accuracy and efficiency.
• Work with cloud platforms (AWS, Azure, or GCP) to deploy and maintain ML/AI models in production.
• Ensure data quality, governance, and compliance with organizational standards.
  
  

Must Have Skill

• 10+ years of relevant experience in Data Science Machine Learning / AI projects.
• Proficiency in Python (pandas, NumPy, scikit-learn, TensorFlow, PyTorch) or R.
• Strong understanding of machine learning algorithms, statistical modeling, and data mining techniques.

• Experience with data visualization tools such as Power BI, Tableau, or Matplotlib/Seaborn.
• Strong SQL skills and experience with data pipelines (Airflow, Spark, etc.).
• Experience with cloud platforms such as AWS SageMaker, Azure ML, or Google AI Platform.
• Excellent analytical, problem-solving, and communication skills.
  
  

Good To Have:

• Experience with Deep Learning, NLP, or Time Series Analysis.
• Exposure to MLOps and CI/CD pipelines for model deployment.
• Certifications or project portfolios in Data Science or Machine Learning
• Experience in prompt engineering, context / RAG engineering, Agentic AI.
  
  

Qualification:

• Bachelor’s or Master’s or PhD degree in Data Science, or a related discipline.

Location:   Hyderabad 

Senior Data Scientist

What You Can Expect from Us:

Here at NomiSo, we work hard to provide our team with the best opportunities to grow their careers.  You can expect to be a pioneer of ideas, a student of innovation, and a leader of thought. Innovation and thought leadership is at the center of everything we do, at all levels of the company. Let’s make your career great!

Position Overview: 

We are looking for an experienced Data Scientist with a strong academic background in Data Science and 8+ years of hands-on experience in Data science projects. The ideal candidate should be skilled in developing predictive models, performing data analysis, and applying advanced machine learning and AI techniques to solve complex business problems.

Roles and Responsibilities:

• Analyze large datasets to extract meaningful insights and patterns.
• Develop, implement, and optimize ML/AI models for predictive and prescriptive analytics
• Collaborate with engineering, product, and business teams to define and deliver data-driven solutions.
• Design and build data pipelines and perform data wrangling using Python, R, or SQL.
• Communicate analytical findings through clear data visualizations and storytelling techniques.
• Evaluate model performance and improve accuracy and efficiency.
• Work with cloud platforms (AWS, Azure, or GCP) to deploy and maintain ML/AI models in production.
• Ensure data quality, governance, and compliance with organizational standards.
  
  

Must Have Skill

• 8+ years of relevant experience in Data Science Machine Learning / AI projects.
• Proficiency in Python (pandas, NumPy, scikit-learn, TensorFlow, PyTorch) or R.
• Strong understanding of machine learning algorithms, statistical modeling, and data mining techniques.
• Experience with data visualization tools such as Power BI, Tableau, or Matplotlib/Seaborn.
• Strong SQL skills and experience with data pipelines (Airflow, Spark, etc.).
• Experience with cloud platforms such as AWS SageMaker, Azure ML, or Google AI Platform.
• Excellent analytical, problem-solving, and communication skills.
  
  

Good To Have:

• Experience with Deep Learning, NLP, or Time Series Analysis.
• Exposure to MLOps and CI/CD pipelines for model deployment.
• Certifications or project portfolios in Data Science or Machine Learning
• Experience in prompt engineering, context / RAG engineering, Agentic AI.
  
  

Qualification:

• Bachelor’s or Master’s or PhD degree in Data Science, or a related discipline.

Location:   Pune / Hyderabad