2,651 Data Driven Solutions jobs in India

Job Summary:

We are seeking a highly skilled and analytical Data Scientist to join our growing team. You will be responsible for extracting insights from large and complex datasets, building predictive models, and supporting data-driven decision-making across the organization. The ideal candidate is passionate about data, has strong statistical and programming skills, and is eager to apply machine learning techniques to real-world problems.

Key Responsibilities:

• Analyze large datasets to uncover trends, patterns, and insights that inform business decisions.
• Design and build predictive models and machine learning algorithms.
• Work closely with stakeholders to understand business challenges and translate them into data-driven solutions.
• Develop dashboards, reports, and data visualizations to communicate findings clearly.
• Validate models and conduct A/B testing to measure impact.
• Collaborate with data engineers to deploy models into production environments.
• Stay up-to-date with the latest data science tools, techniques, and best practices.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related field.
• Proven experience as a Data Scientist or similar role.
• Strong programming skills in Python or R.
• Experience with machine learning frameworks (e.G., scikit-learn, TensorFlow, PyTorch).
• Solid understanding of statistical methods and data modeling techniques.
• Proficiency in SQL and working with relational and non-relational databases.
• Experience with data visualization tools like Tableau, Power BI, or matplotlib/seaborn.
• Excellent problem-solving and communication skills.

Preferred Qualifications:

• Experience with big data tools (e.G., Spark, Hadoop).
• Knowledge of cloud platforms (AWS, GCP, Azure).
• Experience in natural language processing (NLP), time series forecasting, or deep learning.
• Familiarity with data versioning and MLOps practices.

About the Role

We are seeking a seasoned Vice President – Data Analytics to lead our data-driven decision-making, strategy enablement, and operational excellence initiatives.

The role blends strategic problem-solving , data leadership , and business operations acumen , with a mandate to build and scale a high-impact analytics function that partners with business, product, and strategy teams across the organization.

Key Responsibilities

Strategic Leadership

• Define and execute the enterprise-wide data and analytics vision , aligning it with business objectives and growth strategy.
• Partner with C-level leadership to drive data-led business transformation and operational efficiencies.
• Translate strategic goals into measurable outcomes through KPIs, dashboards, and insights.
• Identify opportunities for automation, data monetization, and predictive analytics within core B2B operations.

Data Analytics & Insights

• Lead advanced analytics initiatives including predictive modeling, forecasting, and customer segmentation .
• Develop actionable business insights to drive revenue growth, customer retention, and operational scalability.
• Collaborate with cross-functional teams (Sales, Marketing, Operations, Product, and Finance) to embed analytics into decision-making.
• Oversee the design and implementation of enterprise data infrastructure, ensuring accuracy, governance, and compliance.

Operations & Execution

• Establish a scalable analytics operating model and governance framework.
• Drive adoption of self-service analytics tools and foster a culture of data literacy across business units.
• Manage vendor partnerships and tools for analytics, visualization, and data warehousing.

Stakeholder Management

• Act as a strategic advisor to leadership by delivering insights that influence product strategy, go-to-market models, and operational performance.
• Partner with strategy and finance teams on performance tracking, ROI analysis, and efficiency improvement programs.
• Communicate complex analytical findings in clear, actionable business terms for senior stakeholders.

Key Requirements

• 15+ years of experience in Data Analytics / Strategy / Business Operations.
• Proven track record of building and scaling analytics functions from the ground up .
• Expertise in business strategy, data-driven decision-making, and operational excellence .
• Excellent leadership, stakeholder management, and communication skills

We’re Hiring: Data & AI Product Engineers (3-5 Years Experience;
Hyderanad, IN)

At NuStudio.Ai , we’re building next-gen AI-powered data platforms and immersive digital products , and we’re looking for Data & AI Product Engineers to join our growing team.

What You’ll Do

- Build scalable APIs, data pipelines, and AI-first applications

- Work across cloud, data, and ML platforms to deliver real-time solutions

- Collaborate with designers, product teams, and ML engineers to ship impactful features

What We’re Looking For

- 3–5 years of software/data engineering experience

- Strong in Python, SQL, JavaScript/TypeScript (React a plus)

- Hands-on with Spark, Kafka, Databricks, or BigQuery

- Solid grasp of APIs, microservices, and cloud-native architectures

Bonus Skills

- Experience with ML pipelines, GenAI, or IoT/edge systems

- Exposure to LangChain, LLMOps, or GenAI-powered applications

Apply:

Learn more:

Join us in building the future of AI-driven products.

#WeAreHiring #AIJobs #Engineering #DataEngineering #Python #React #StartupJobs #TechJobs #Databricks #Spark #Kafka #Cloud #MachineLearning #JoinOurTeam

Shift Ahead is seeking an Independent Data Specialist responsible for creating autonomous AI systems— —that can discuss on client calls, understand needs and plan, reason, learn, and act independently or collaboratively across dynamic real-world or simulated environments

Expertise in Data domain

EXPERIENCE IN Data/AI side of data modelling. Need a strong front end person on Data (data modelling) for Azure, Databricks, Snowflakes, etc

Key Responsibilities

• Design and Develop on Interoperability, Data ingestion, Data normalisation
• Structured & Non structured data management
• Semantic layer creation
• API integration
• Create agentic systems with capabilities for autonomous decision-making, task decomposition, and adaptive behaviors.
• Design and implement cognitive architectures, memory systems, and planning algorithms to enable self-reflective, goal-driven agents.
• Integrate large language models (LLMs), symbolic reasoning, and generative AI components into cohesive agent frameworks.

Collaboration & Deployment

• Work closely with cross-functional teams in product, UX, robotics, cloud engineering, and data science.

Deploy agentic AI solutions at scale in production, ensuring robust, efficient, and secure environments

Experience

• 4+ years of experience in AI/ML development with a focus on autonomous agents or AI planning.
• Proven hands-on experience with agentic frameworks such as LangChain, AutoGen, or similar custom agent toolkits.
• Sound Experience working with LLMs, transformers, RAG pipelines, and model fine-tuning.

Python proficiency required;
knowledge of AI/ML libraries (PyTorch, TensorFlow, Hugging Face). Familiarity with cloud environments (AWS, GCP, Azure) and vector databases (Pinecone, Milvus, Chroma) is highly desirable

Should be flexible, commited consultants also welcome for shorter hours per week

Confident candidates ready to work independently may also contact or mail to

• Position Title –Data Analytics Manager
• Location – Bengaluru-Corporate Office
• Total Experience of 4 to 10 Years
• Qualification – Bachelor's in data science & Statistics, Computer Science, or bachelor's in Engineering
• Direct Reporting – Nil (Individual Contributor)
• Industry- FMCD (Small Appliances, preferably)/FMCG/FMEG/Luggage /Building Material/ Retail

Key Responsibilities:-

Data Analysis and Reporting:

• Be the central point for all business and performance analytics
• Oversee the collection, processing, and interpretation of large datasets
• Manage all MIS and reports for various functions and ensure timely delivery of reports to each function.
• Develop self-serve BI tools and automated reporting for functional leaders
• Identify trends, patterns, and insights to drive strategic decision-making
• Build and maintain executive dashboards to monitor business health and performance metrics.

Data Strategy Development:

• Develop and implement data analytics strategies to support business objectives.
• Partner with the Head of Strategy to define KPIs, track strategic projects, and measure business performance.
• Collaborate with other departments to understand their data needs and provide actionable insights.

Team Management:

• Led and mentored a team of data analysts and MIS experts
• Ensured projects were completed on time and within budget
• Foster a collaborative and innovative work environment

Tool and System Management:

• Implement and maintain data analytics tools and systems
• Ensure the efficient operation of data collection and analysis processes
• Troubleshoot and resolve any issues related to data systems
• Use statistical methods, predictive modeling, and data mining techniques to inform decision-making
• Provide ROI analysis on transformation and cost-saving initiatives

Stakeholder Communication:

• Act as the analytics point of contact for strategy-related initiatives
• Work with product, IT, supply chain, and marketing teams to gather data and align KPIs.
• Present insights and recommendations to senior leadership in a clear and compelling manner

Other Responsibilities:

• Delivery of data services to support marketing activities
• Program and develop Extract, Transform and Load programs to support integration
• Ensure data quality within the database - Data Loading and error handling
• User Acceptance Test to ensure Quality in deliverables
• Produce high standard of documentation on data flows and processes
• Coordinated data campaigns and analysis projects, including segmentation and modeling deliverables.
• Assess client and 3rd party data sources and new data capture opportunities to enhance existing data.
• Defined and set up reporting and analysis processes and deliverables that meet client objectives.

Key Performance Indicator:-

• Data Accuracy : Accuracy and reliability of data collected and analyzed
• Insight Utilization : Percentage of business decisions influenced by data insights
• Project Timeliness : Completion of data projects within the agreed timelines
• Team Performance : Productivity and development of the data analytics team
• Stakeholder Satisfaction : Feedback from stakeholders on the usefulness and clarity of data insights
• Familiarity with cloud data platforms (e.G., Azure, AWS, Google BigQuery)

Remarks:-

• Experience working with ERP & CRM systems such as SAP, Salesforce or similar Strong command of SQL, Excel, and at least one scripting language (Python, R, etc.)
• Proven experience building dashboards (Power BI, Tableau, QlikView, etc.) and working with large data sets.
• Knowledge of data management best practices and regulatory requirements.
• Knowledge of data management best practices and regulatory requirements.
• Good Communication & Influencing Skills.
• Looking for stable candidates only (Frequent job changes will be not considered).
• Local Candidates will be preferred

Principal Product Manager, AI & Industrial Data Contextualization

Cognite is building a new team in Bengaluru, India, focused on developing cutting-edge tools for contextualizing industrial data within our core platform, Cognite Data Fusion (CDF) . We are seeking a Principal Product Manager to lead this strategic initiative, driving the vision, strategy, and execution for a product area at the intersection of industrial operations, data, and advanced AI.

Cognite Data Fusion is a foundational Industrial DataOps platform that runs on all major hyperscalers—AWS, Azure, and Google Cloud—and is deployed globally to many regions across the world. Our platform is used by a diverse range of customers spanning multiple industries, from those engaged in batch production and continuous production to companies in oil & gas and discrete manufacturing . Your work on contextualization will be crucial for empowering these customers, regardless of their industrial process.

Role Overview

As a Principal Product Manager, you'll be responsible for defining and delivering the next generation of our contextualization tools. This isn't about traditional data integration;
it's about harnessing the power of AI to transform how industrial data, particularly engineering diagrams and unstructured documents, is understood and connected. You'll lead the charge in shifting from deterministic, rule-based systems to intelligent, self-correcting, and probabilistic AI-driven solutions that drastically reduce manual effort and improve data quality for our customers.

You'll act as the key link between our engineering team in Bengaluru, our internal global stakeholders and our global customer base. You'll work closely with customers to understand their challenges, define product requirements, and guide the team in building scalable, user-centric solutions. This role requires a blend of deep technical expertise in machine learning and a strong product management mindset focused on user outcomes and market needs.

Key Responsibilities

• Define Product Strategy: Develop and own the product vision and strategy for AI-driven contextualization, aligning it with Cognite's overall mission and market opportunities.
• Lead with Empathy: Engage with customers and internal stakeholders to deeply understand their problems, pain points, and workflows related to digitizing and connecting data.
• Translate Vision to Execution: Author detailed product requirements and user stories for the engineering team, ensuring a clear and shared understanding of goals. You'll be instrumental in prioritizing the product backlog to maximize impact.
• Navigate the AI Landscape: Drive the adoption of advanced machine learning techniques, including computer vision models (e.G., Faster R-CNN, YOLO, Siamese Networks ), and other AI/ML approaches for symbol, text, and line detection in engineering diagrams.
• Champion a Shift in Mindset: Lead the transition from manual, deterministic methods to intelligent, probabilistic, and agentic workflows that can self-correct and optimize based on user-defined expectations rather than rigid, manual configurations.
• Manage Cross-functional Collaboration: Work closely with engineering, UX/UI, data science, and customer-facing teams to deliver a cohesive product experience. You'll also need to navigate the complexities of a multi-cloud environment, considering platform services from AWS, Azure, and GCP.
• Build the Team: Play a key role in hiring and mentoring product managers and other talent as the team grows in Bengaluru.

Required Skills & Experience

• Priority 1: AI-Driven Product Development & Market Launch: Proven experience in a product leadership role for AI/ML-driven products. You must have a demonstrated track record of launching successful AI products to market at scale. You should have a solid understanding of machine learning concepts, including model training, data sets, feature extraction, and different model architectures like convolutional neural networks.
• Priority 2: Industrial Data Expertise: Experience in the industrial sector is highly desirable. You should have a strong understanding of industrial data domains, including engineering data, sensor data, and data from ERP and MES systems . Familiarity with relevant industry standards is a significant advantage, including but not limited to:
• Engineering and Asset Data: DEXPI, CFIHOS, ISO 14224, ISO 15926
• Enterprise and Business Data: ISA-95, B2MML
• Product and Classification Data: ECLASS, UNSPSC, GPC
• Data-Centric AI Leadership: You have a proven track record of managing and leading teams that prioritize data quality and are structured for success with probabilistic models. This includes experience with:
• Data Collection & Labeling: Successfully managing the collection, curation, and labeling of huge volumes of complex data.
• Data-First Methodology: Implementing a test-driven AI/ML methodology using evaluation and benchmark datasets to drive continuous model improvement and measure performance.
• AI-Driven Configuration: A strong understanding of how to use AI to optimize product configurations based on user-described success metrics, moving beyond manual parameter tuning.
• Hands-on Experience with AI Projects: Direct experience leading projects involving computer vision and object detection, ideally on complex industrial imagery or technical diagrams. Knowledge of techniques for synthetic data generation and fine-tuning models on limited, proprietary data is a significant advantage.
• Product Management Acumen: A minimum of 8 years of product management experience, with a track record of successfully bringing complex technical products to market.
• Cloud Computing and Multi-cloud Solutions: Experience with cloud platforms such as AWS, Azure, and/or Google Cloud. A strong understanding of how to build and manage products that can be deployed across different cloud providers is essential. Relevant services include:
• AWS: SageMaker, Lambda, Bedrock Data Automation, Textract
• Azure: Azure Machine Learning, Azure Functions, Azure AI Document Intelligence
• GCP: Google Cloud Vertex AI, Google Cloud Functions, Google Cloud Document AI
• Technical Communication: The ability to communicate complex technical concepts to both technical and non-technical audiences, translating AI capabilities into tangible business value.

Strategic Thinking: The ability to think beyond current solutions and envision a future where AI radically simplifies industrial data management. You should be able to define what "good" is and establish metrics to measure success.

Greetings from Live Connections !