410 Data Science Positions jobs in Noida
Data Science Specialist
Posted 10 days ago
Job Viewed
Job Description
About Tavant:
With 25+ years of experience building innovative digital products and solutions, Tavant provides impactful results to its customers. It has been the frontrunner in driving digital innovation and tech-enabled transformation across a wide range of industries such as Consumer Lending, Manufacturing, Agtech, Media & Entertainment, and Retail in North America, Europe, and Asia-Pacific. Powered by Artificial Intelligence and Machine Learning algorithms, we help our customers improve their operational efficiency, productivity, speed, and accuracy. Our suite of products and solutions are routinely rated high by the industry.
Ours is a challenging workplace where teams are diverse, competitive, and continually searching for tomorrow's technology and brilliant minds to create it. And we don’t focus just on what we do – we also care how we do it. So, bring your talent and ambition to make a difference. We’ll create a world of opportunities for you.
Job Title : Lead Data Science Consultant
Experience : 15-20 years
Work Location : Bangalore/Hyderabad/Noida/Kolkata/Pune
Work mode : Hybrid (3 days WFO)
We are looking for an experienced Senior Lead Data Scientist / ML Engineer with a strong blend of pre-sales expertise, team leadership, and technical proficiency across classical machine learning, deep learning, and generative AI. You will engage in high-level client discussions, drive technical sales strategies, and lead a team to design and implement cutting-edge ML solutions. This is a strategic role requiring both thought leadership and hands-on technical contributions.
Key Responsibilities
Pre-Sales & Client Engagement
- Collaborate with the sales and business development teams to identify client needs and formulate AI/ML solutions.
- Present technical concepts, project proposals, and proof-of-concepts (POCs) to prospects and clients.
- Translate complex client requirements into actionable project scopes, estimates, and technical proposals.
Leadership & Team Management
- Provide direction, mentorship, and performance feedback to a team of data scientists and ML engineers.
- Establish best practices in solution design, code reviews, model validation, and production deployment.
- Drive the strategic roadmap for AI initiatives, ensuring alignment with organizational goals and market trends.
Classical Machine Learning & Statistical Modeling
- Apply classical machine learning techniques (e.g., regression, clustering, decision trees, ensemble methods) to solve diverse business problems.
- Design and optimize data pipelines, feature engineering processes, and model selection strategies.
- Ensure robust model evaluation, tuning, and performance monitoring in production environments.
Deep Learning & Generative AI
- Develop and maintain deep learning models using frameworks such as TensorFlow or PyTorch for tasks like computer vision, NLP, or recommendation systems.
- Explore and build solutions leveraging generative AI (GANs, VAEs, or transformer-based architectures) for innovative product features and services.
- Champion research and experimentation with state-of-the-art AI models, staying ahead of industry advances.
Project Delivery & MLOps
- Lead end-to-end ML project lifecycles, from data exploration and model development to deployment and post-launch maintenance.
- Implement MLOps best practices (CI/CD, containerization, model versioning) on cloud or on-premise infrastructures.
- Collaborate with DevOps and engineering teams to integrate ML solutions seamlessly into existing systems.
Stakeholder Management & Communication
- Serve as a key technical advisor to executive leadership, product managers, and client teams.
- Communicate complex AI/ML findings in clear, actionable terms to both technical and non-technical audiences.
- Advocate data-driven decision-making and foster a culture of innovation within the organization.
Required Qualifications
Education & Experience
- Master’s or PhD in Computer Science, Data Science, Engineering, or a related field is preferred.
- 12+ years of relevant industry experience in data science or ML engineering, with 5+ years in a leadership or management capacity.
Technical Expertise
- Pre-Sales: Demonstrated experience in client-facing roles, solutioning, and proposal development.
- Classical ML: Skilled in traditional algorithms (regression, classification, clustering, etc.) and statistical methods.
- Deep Learning: Hands-on expertise with frameworks (e.g., TensorFlow, PyTorch) for CNNs, RNNs, transformer architectures, etc.
- Generative AI: Practical exposure to GANs, VAEs, or large language models, with a track record of building generative models.
- MLOps: Familiarity with CI/CD pipelines, Docker/Kubernetes, and cloud platforms (AWS, Azure, GCP).
Leadership & Communication
- Proven ability to mentor and lead data science/ML engineering teams to meet project goals.
- Exceptional communication skills for presenting to clients, stakeholders, and executive leadership.
- Experience in agile methodologies and project management, balancing multiple projects simultaneously.
Preferred / Bonus Skills
- Experience in big data ecosystems (Spark, Hadoop) for large-scale data processing.
- Background in NLP, computer vision, or recommendation systems.
- Knowledge of DevOps tools (Jenkins, GitLab CI, Terraform) for infrastructure automation.
- Track record of published research or contributions to open-source AI projects.
Director Data Science
Posted 16 days ago
Job Viewed
Job Description
B.E with 15+ experience in data Science / AI space.
About the Role
Be a leader in ML & GenAI Space with exposure to Application building.
Responsibilities
- Should have experience in doing Business Development on ML & GenAI space.
- Should have exposure in independently creating demos, PoC’s and accelerators on GenAI space.
- Able to handle entire BD process of its own.
- Can setup a team of smart data scientists and app developers quickly.
- Be an Individual Contributor in the Analytics and Development team and solve real-world problems using cutting-edge capabilities and emerging technologies based on LLM/GenAI/GPT.
- Software development experience in python is needed as backend for UI based applications.
- Create Technical documents e.g., HLD/LLDs/Technical Designs etc., develop, test, and deploy data analytics processes using Python, SQL on Azure/AWS platforms.
- Can interact with client on GenAI related capabilities and use cases.
Qualifications
B.E with 15+ experience in data Science / AI space.
Required Skills
- Experience in ML & GenAI space.
- Business Development experience.
- Software development experience in Python.
- Experience with Azure/AWS platforms.
Data Science Specialist
Posted today
Job Viewed
Job Description
About Tavant:
With 25+ years of experience building innovative digital products and solutions, Tavant provides impactful results to its customers. It has been the frontrunner in driving digital innovation and tech-enabled transformation across a wide range of industries such as Consumer Lending, Manufacturing, Agtech, Media & Entertainment, and Retail in North America, Europe, and Asia-Pacific. Powered by Artificial Intelligence and Machine Learning algorithms, we help our customers improve their operational efficiency, productivity, speed, and accuracy. Our suite of products and solutions are routinely rated high by the industry.
Ours is a challenging workplace where teams are diverse, competitive, and continually searching for tomorrow's technology and brilliant minds to create it. And we don’t focus just on what we do – we also care how we do it. So, bring your talent and ambition to make a difference. We’ll create a world of opportunities for you.
Job Title : Lead Data Science Consultant
Experience : 15-20 years
Work Location: Bangalore/Hyderabad/Noida/Kolkata/Pune
Work mode: Hybrid (3 days WFO)
We are looking for an experienced Senior Lead Data Scientist / ML Engineer with a strong blend of pre-sales expertise, team leadership, and technical proficiency across classical machine learning, deep learning, and generative AI. You will engage in high-level client discussions, drive technical sales strategies, and lead a team to design and implement cutting-edge ML solutions. This is a strategic role requiring both thought leadership and hands-on technical contributions.
Key Responsibilities
Pre-Sales & Client Engagement
- Collaborate with the sales and business development teams to identify client needs and formulate AI/ML solutions.
- Present technical concepts, project proposals, and proof-of-concepts (POCs) to prospects and clients.
- Translate complex client requirements into actionable project scopes, estimates, and technical proposals.
Leadership & Team Management
- Provide direction, mentorship, and performance feedback to a team of data scientists and ML engineers.
- Establish best practices in solution design, code reviews, model validation, and production deployment.
- Drive the strategic roadmap for AI initiatives, ensuring alignment with organizational goals and market trends.
Classical Machine Learning & Statistical Modeling
- Apply classical machine learning techniques (e.g., regression, clustering, decision trees, ensemble methods) to solve diverse business problems.
- Design and optimize data pipelines, feature engineering processes, and model selection strategies.
- Ensure robust model evaluation, tuning, and performance monitoring in production environments.
Deep Learning & Generative AI
- Develop and maintain deep learning models using frameworks such as TensorFlow or PyTorch for tasks like computer vision, NLP, or recommendation systems.
- Explore and build solutions leveraging generative AI (GANs, VAEs, or transformer-based architectures) for innovative product features and services.
- Champion research and experimentation with state-of-the-art AI models, staying ahead of industry advances.
Project Delivery & MLOps
- Lead end-to-end ML project lifecycles, from data exploration and model development to deployment and post-launch maintenance.
- Implement MLOps best practices (CI/CD, containerization, model versioning) on cloud or on-premise infrastructures.
- Collaborate with DevOps and engineering teams to integrate ML solutions seamlessly into existing systems.
Stakeholder Management & Communication
- Serve as a key technical advisor to executive leadership, product managers, and client teams.
- Communicate complex AI/ML findings in clear, actionable terms to both technical and non-technical audiences.
- Advocate data-driven decision-making and foster a culture of innovation within the organization.
Required Qualifications
Education & Experience
- Master’s or PhD in Computer Science, Data Science, Engineering, or a related field is preferred.
- 12+ years of relevant industry experience in data science or ML engineering, with 5+ years in a leadership or management capacity.
Technical Expertise
- Pre-Sales: Demonstrated experience in client-facing roles, solutioning, and proposal development.
- Classical ML: Skilled in traditional algorithms (regression, classification, clustering, etc.) and statistical methods.
- Deep Learning: Hands-on expertise with frameworks (e.g., TensorFlow, PyTorch) for CNNs, RNNs, transformer architectures, etc.
- Generative AI: Practical exposure to GANs, VAEs, or large language models, with a track record of building generative models.
- MLOps: Familiarity with CI/CD pipelines, Docker/Kubernetes, and cloud platforms (AWS, Azure, GCP).
Leadership & Communication
- Proven ability to mentor and lead data science/ML engineering teams to meet project goals.
- Exceptional communication skills for presenting to clients, stakeholders, and executive leadership.
- Experience in agile methodologies and project management, balancing multiple projects simultaneously.
Preferred / Bonus Skills
- Experience in big data ecosystems (Spark, Hadoop) for large-scale data processing.
- Background in NLP, computer vision, or recommendation systems.
- Knowledge of DevOps tools (Jenkins, GitLab CI, Terraform) for infrastructure automation.
- Track record of published research or contributions to open-source AI projects.
FACULTY DATA SCIENCE
Posted today
Job Viewed
Job Description
URGENT HIRING FOR
DATA SCIENCE AND ANAYLST FACULTY & TRAINEE AT VERIDICAL TECHNOLOGIES, PITAMPURA (DELHI- )
POSITIONS : TWO (2)
Role Description
This is a full-time, on-site Faculty Data Science role located in Delhi, India. The Faculty Data Science will be responsible for providing project based training and guidance to students, creating course materials and assessments, and staying updated with the latest industry trends and practices.
Qualifications
- Strong knowledge of Data Science concepts, including Machine Learning, Deep learning, NLP, LLM & GEN AI
- Experience with programming languages such as Python, R, and SQL
- Ability to develop and deliver curriculum content effectively
- Excellent communication and presentation skills
Experience
- Minimum 2 years teaching experience
- Master's degree in Data Science
- A passion for teaching and mentoring students
- Strong analytical and problem-solving skills
KEY AREAS TO PONDER:
IMMEDIATE JOINING
FACE TO FACE INTERVIEW PREF.
CERTIFICATES FROM EDTECH ONLINE FREE TRAINING PROGRAMS ARE NOT ACCEPTED.
HONEST CANDIDATE WITH GOOD MORAL, ETHICAL & PROFESSIONAL VALUES ARE REQUIRED.
SALARY : RANGE FROM 15K TO 40K ( TRAINEE TO FACULTY)
VENUE: AGGARWAL PRESTIGE MALL, 512, 5TH FLOOR, RANI BAGH, ROAD NO. 44, PITAMPURA, DELHI -
DROP YOUR CV AT
contact no.:
Director Data Science
Posted today
Job Viewed
Job Description
B.E with 15+ experience in data Science / AI space.
About the Role
Be a leader in ML & GenAI Space with exposure to Application building.
Responsibilities
- Should have experience in doing Business Development on ML & GenAI space.
- Should have exposure in independently creating demos, PoC’s and accelerators on GenAI space.
- Able to handle entire BD process of its own.
- Can setup a team of smart data scientists and app developers quickly.
- Be an Individual Contributor in the Analytics and Development team and solve real-world problems using cutting-edge capabilities and emerging technologies based on LLM/GenAI/GPT.
- Software development experience in python is needed as backend for UI based applications.
- Create Technical documents e.g., HLD/LLDs/Technical Designs etc., develop, test, and deploy data analytics processes using Python, SQL on Azure/AWS platforms.
- Can interact with client on GenAI related capabilities and use cases.
Qualifications
B.E with 15+ experience in data Science / AI space.
Required Skills
- Experience in ML & GenAI space.
- Business Development experience.
- Software development experience in Python.
- Experience with Azure/AWS platforms.
Data Science Consultant
Posted today
Job Viewed
Job Description
•Experience in data processing tools such as Talend processing data formats such as CSV, XML, JSON, etc would be required.
•The ability to combine big data with traditional relational databases such as SQL Server or Oracle would be an advantage for the role.
•The ability to program in Python and an awareness of common libraries and how they are used is beneficial.
•Awareness of Tableau or equivalent visualization tools and associated concepts would be beneficial as these are used extensively by the Research Line of Business.
•Awareness of Natural Language Processing models, techniques, and concepts would be advantageous as this is a growth area for the Line of Business.
•Awareness of the Cloudera big data technology stack and an understanding of big data concepts and demonstrable experience of retrieving data, joining data, and managing data in a Hadoop database via tools such as HUE would be an asset.
•A good understanding of ETL tools used on big data platforms and demonstrable experience in creating and managing data pipelines would be essential for this role.
Candidate should have
• Experience working with ETL, Python, Hadoop, Talend.
•Prior experience working in the financial industry is highly preferred.
Data Science Engineer
Posted today
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Job Description
• .Use machine learning, statistical, and programming skills to enable data analytics.
• Drive informed decision-making and present findings to both technical and non-technical audiences.
• Work closely with physicians to identify medically relevant use cases, develop machine learning models, and validate impact.
• Deliver insights and values from heterogeneous data to investigate complex problems in the health care domain for multiple use cases
• Provide technical direction and mentor junior members of the Medical Informatics team.
• Work closely with software engineers to facilitate model integration and deployment.
• Embrace a fast-paced, collaborative environment dedicated to building atop cutting-edge technology.
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Data Science Solutions
Posted today
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Job Description
• Design and integrate data from different sources.
• Forms analytics platform components and processing components required to provide a business solution.
• Engage with business stakeholders to design and own end-to-end solutions to empower data-driven decision-making.
• Lead the design, implementation, and continuous delivery of an insights data pipeline supporting the development and operation of custom analytic products/services across the organization.
• Ensures appropriate data testing is completed and meets test plan requirements.