Analytics jobs in India

The role is a pivotal position in the organisation, requiring a dedicated professional adept at monitoring and driving initiatives to control costs across business verticals working within the CFO's Office.

The client is seeking a dynamic Digital Analytics Leader to shape its global digital future by building and driving digital analytics and AI practices, delivering insights, and enabling enterprise-wide automation. The role will leverage current and emerging technologies to transform client's business, driving intelligent automation solutions and shaping the AI/ML, analytics, and reporting strategy.

Build and maintain data platform for the organization

• Lead advanced analytics initiatives focused on predictive and demand forecasting, market mix modelling (MMM), and business insights.
• Engage with cross-functional teams and senior leadership to drive data-backed decision-making

• 6+ years of experience in Business Intelligence and data analysis.
• 3+ years of hands-on experience developing solutions using Power BI.
• Expert-level DAX knowledge with proven experience in optimizing complex queries.

The purpose of the Data Engineering specialist is to build and unit test code for Projects and Programmes on Azure Cloud Data and Analytics Platform

This position involves the management of HR Operations and Analytics, with a particular focus on streamlining processes and leveraging data to drive strategic initiatives within a financial services setting. The successful candidate will have a unique blend of business focus, strong analytical and problem-solving skills and programming knowledge to enable efficient HR operations.

This position is responsible for to define and align analytics vision, manage execution of data initiatives, lead data talents, drive analytics maturity and ensure the business is powered by data solution. He/She will also facilitate analytics use-cases generation, lead selection and prioritization and oversee validation process. The position serves as an advisor to the leadership team.

- This role focuses on supporting strategic HR projects with an emphasis on compensation, people analytics and talent management.

- It involves analyzing HR data, conducting benchmarking and driving initiatives like org design, job evaluation and workforce planning to support business goals.

You will have a key role in advancing how GIA utilises available data for its risk assessment and assurance planning, aiming to integrate this into a real-time data-led ecosystem. Your responsibilities include driving innovation and increasing the productivity of the audit function through the use of data, developing predictive models and use of Data Science techniques in the department.

elta Lake, and Unity Catalog-all on Azure Cloud. You'll play a critical role in ensuring data security (PII encryption), governance, and cost optimization, while mentoring a talented team of engineers.

The Senior Demand Planner Analyst must demonstrate the ability to effectively lead their respective staff in properly plan for shifts in consumer purchasing, while optimizing product inventory levels. Product forecasting will be managed in Relex (inventory planning system), interfacing with Merchants and Vendors for their assigned area of business, ensuring proper planning for item introductions, promotions, item discontinuation, and more.

Lead the design and continuous improvement of Data Science programs, ensuring academic excellence and industry relevance. Manage and mentor faculty, delivered impactful sessions, and represent Hero Vired at conferences and external forums. Further, establish and uphold academic rigor and delivery excellence across diverse learning formats (online, hybrid, live).

• End-to-end ownership of digital and AI transformation across functions
• Direct collaboration with CXOs and business heads on high-visibility programs
• Opportunity to build and scale an intelligent AI ecosystem in partnership with Heads of Data, Analytics,

We are looking for a customer-focused & business-oriented Data Scientist who will be responsible for conducting analyses using advanced statistics and data mining techniques to enable better decision-making.

As a Data Analyst within our Data & Analytics Team, you will be a crucial partner to the business. Collaborating closely with our business teams across divisions, you will leverage data to drive strategic decision-making and optimize operational efficiency.

Job Description: looking for a talented and experienced Senior Data Engineer with a strong expertise in Snowflake to join our team. As a Senior Data Engineer, you will play a critical role in the development and optimisation of data systems, data pipelines, and ensuring seamless data transformations to support business intelligence and data-driven decisions.

Position:

ML EngineerJob type:

Techno-FunctionalPreferred education qualifications:

Bachelor/ Master's degree in computer science, Data Science, Machine Learning OR related technical degreeJob location:

IndiaGeography:

SAPMENARequired experience:

6-8 YearsPreferred profile/ skills:

• 5+ years in developing and deploying enterprise-scale ML solutions
• [Mandatory] Proven track record in data analysis (EDA, profiling, sampling), data engineering (wrangling, storage, pipelines, orchestration),
• [Mandatory] Proficiency in Data Science/ML algorithms such as regression, classification, clustering, decision trees, random forest, gradient boosting, recommendation, dimensionality reduction
• [Mandatory] Experience in ML algorithms such as ARIMA, Prophet, Random Forests, and Gradient Boosting algorithms (XGBoost, LightGBM, CatBoost)
• [Mandatory] Prior experience on MLOps with Kubeflow or TFX
• [Mandatory] Experience in model explainability with Shapley plot and data drift detection metrics.
• [Mandatory] Advanced programming skills with Python and SQL
• [Mandatory] Prior experience on building scalable ML pipelines & deploying ML models on Google Cloud
• [Mandatory] Proven expertise in ML pipeline optimization and monitoring the model's performance over time
• [Mandatory] Proficiency in version control systems such as GitHub
• Experience with feature engineering optimization and ML model fine tuning is preferred
• Google Cloud Machine Learning certifications will be a big plus
• Experience in Beauty or Retail/FMCG industry is preferred
• Experience in training with large volume of data (>100 GB)
• Experience in delivering AI-ML projects using Agile methodologies is preferred
• Proven ability to effectively communicate technical concepts and results to technical & business audiences in a comprehensive manner
• Proven ability to work proactively and independently to address product requirements and design optimal solutions
• Fluency in English, strong communication and organizational capabilities; and ability to work in a matrix/ multidisciplinary team

Job objectives:

Design, develop, deploy, and maintain data science and machine learning solutions to meet enterprise goals. Collaborate with product managers, data scientists & analysts to identify innovative & optimal machine learning solutions that leverage data to meet business goals. Contribute to development, rollout and onboarding of data scientists and ML use-cases to enterprise wide MLOps framework. Scale the proven ML use-cases across the SAPMENA region. Be responsible for optimal ML costs.Job description:

• Deep understanding of business/functional needs, problem statements and objectives/success criteria
• Collaborate with internal and external stakeholders including business, data scientists, project and partners teams in translating business and functional needs into ML problem statements and specific deliverables
• Develop best-fit end-to-end ML solutions including but not limited to algorithms, models, pipelines, training, inference, testing, performance tuning, deployments
• Review MVP implementations, provide recommendations and ensure ML best practices and guidelines are followed
• Act as 'Owner' of end-to-end machine learning systems and their scaling
• Translate machine learning algorithms into production-level code with distributed training, custom containers and optimal model serving
• Industrialize end-to-end MLOps life cycle management activities including model registry, pipelines, experiments, feature store, CI-CD-CT-CE with Kubeflow/TFX
• Accountable for creating, monitoring drifts leveraging continuous evaluation tools and optimizing performance and overall costs
• Evaluate, establish guidelines, and lead transformation with emerging technologies and practices for Data Science, ML, MLOps, Data Ops

Job RequirementsEducation

* Bachelor's degree required, preferably with a quantitative focus (Statistics, Business Analytics, Data Science, Math, Economics, etc.)

* Master's degree preferred (MBA/MS Computer Science/M.Tech Computer Science, etc.)Relevant Experience

* 5 - 7 years for Data Scientist

* Relevant working experience in a data science/advanced analytics roleBehavioural Skills

* Delivery Excellence

* Business disposition

* Social intelligence

* Innovation and agilityExperience

* Functional Analytics (Supply chain analytics, Marketing Analytics, Customer Analytics, etc.)

* Statistical modelling using Analytical tools (R, Python, KNIME, etc.)

* Knowledge of statistics and experimental design (A/B testing, hypothesis testing, causal inference)

* Practical experience building scalable ML models, feature engineering, model evaluation metrics, and statistical inference.

* Practical experience deploying models using MLOps tools and practices (e.g., MLflow, DVC, Docker, etc.)

* Strong coding proficiency in Python (Pandas, Scikit-learn, PyTorch/TensorFlow, etc.)

* Big data technologies & framework (AWS, Azure, GCP, Hadoop, Spark, etc.)

* Enterprise reporting systems, relational (MySQL, Microsoft SQL Server etc.), non-relational (MongoDB, DynamoDB) database management systems and Data Engineering tools

* Business intelligence & reporting (Power BI, Tableau, Alteryx, etc.)

* Microsoft Office applications (MS Excel, etc.)Roles & Responsibilities

Analytics & Strategy

1. Analyse large-scale structured and unstructured data; develop deep-dive analyses and machine learning models in retail, marketing, merchandising, and other areas of the business

2. Utilize data mining, statistical and machine learning techniques to derive business value from store, product, operations, financial, and customer transactional data

3. Apply multiple algorithms or architectures and recommend the best model with in-depth description to evangelize data-driven business decisions

4. Utilize cloud setup to extract processed data for statistical modelling and big data analysis, and visualization tools to represent large sets of time series/cross-sectional dataOperational Excellence

1. Follow industry standards in coding solutions and follow programming life cycle to ensure standard practices across the project

2. Structure hypothesis, build thoughtful analyses, develop underlying data models and bring clarity to previously undefined problems

3. Partner with Data Engineering to build, design and maintain core data infrastructure, pipelines and data workflows to automate dashboards and analysesStakeholder Engagement

1. Working collaboratively across multiple sets of stakeholders - Business functions, Data Engineers, Data Visualization experts to deliver on project deliverables

2. Articulate complex data science models to business teams and present the insights in easily understandable and innovative formats

Job Requirements Education

* Bachelor's degree required, preferably with a quantitative focus (Statistics, Business Analytics, Data Science, Math, Economics, etc.)

* Master's degree preferred (MBA/MS Computer Science/M.Tech Computer Science, etc.) Relevant Experience

*3 - 4 years for Data Scientist

* Relevant working experience in a data science/advanced analytics role Behavioural Skills

*Delivery Excellence

*Business disposition

*Social intelligence

*Innovation and agility Knowledge

* Functional Analytics (Supply chain analytics, Marketing Analytics, Customer Analytics, etc.)

*Statistical modelling using Analytical tools (R, Python, KNIME, etc.)*Knowledge of statistics and experimental design (A/B testing, hypothesis testing, causal inference)

*Practical experience building scalable ML models, feature engineering, model evaluation metrics, and statistical inference.

*Practical experience deploying models using MLOps tools and practices (e.g., MLflow, DVC, Docker, etc.)

*Strong coding proficiency in Python (Pandas, Scikit-learn, PyTorch/TensorFlow, etc.)

*Big data technologies & framework (AWS, Azure, GCP, Hadoop, Spark, etc.)

* Enterprise reporting systems, relational (MySQL, Microsoft SQL Server etc.), non-relational (MongoDB, DynamoDB) database management systems and Data Engineering tools

*Business intelligence & reporting (Power BI, Tableau, Alteryx, etc.)

* Microsoft Office applications (MS Excel, etc.)

Location- Gurgaon

Be a thought leader for a large MNC with high stakes in the AI development

Be hands-on 100% and leverage the ecosystem for innovation available

You will have a key role in advancing how GIA utilises available data for its risk assessment and assurance planning, aiming to integrate this into a real-time data-led ecosystem. Your responsibilities include driving innovation and increasing the productivity of the audit function through the use of data, automation, predictive models, and AI. Additionally, you will be responsible for establishing a local team with direct line management duties.

The client is a experienced Data Modeler specialising in scalable data model design for HRIS and IAM systems. The person will translate business needs into robust conceptual, logical and physical models supporting both transactional and analytical use cases. They'll collaborate with cross-functional teams to define data architecture, ensure governance and compliance, and optimize ETL pipelines.

This role involves spearheading transformation initiatives within the industry to align business processes with strategic goals. As a Transformation Manager, you will collaborate across departments to drive innovation and process improvements in a manufacturing environment.

Your Responsibilities

• Develop, optimize, and deploy embedded machine learning models.
• Ensure performance, memory optimization, and energy efficiency of AI solutions.
• Integrate ML algorithms with embedded controllers and edge computing platforms.
• Collaborate closely with automation and software engineers to translate AI solutions into production-grade embedded systems.

Our Requirements

• Degree in Computer Science, Electrical Engineering, or related field.
• Strong proficiency in Python, C/C++, and embedded programming.
• Experience with embedded ML frameworks (e.g., TensorFlow Lite, ONNX, Edge Impulse).
• Understanding of real-time embedded systems and microcontroller architectures.
• Minimum of 2 years of relevant experience with Embedded Systems and AI/ML

Job Location: Bengaluru, India
Job Type: Full-time
Experience: 2+ years

As the Head of AI, you'll be at the forefront of developing advanced AI systems across NLP, Computer Vision, and Recommendation Engines, all while leading and mentoring a world-class team

3+ years of Proven experience in developing dashboards using Tableau, with a strong passion for data analysis and Excellent communication skills and hands-on expertise in Python.

• Lead and manage the delivery of data projects, ensuring timely execution and quality standards.
• Collaborate with business and technical teams to define project scope, timelines, and milestones.

This role requires a highly organized and experienced individual to lead and manage complex data-centric programs, incorporating strong change management principles and process analysis capabilities. The Data Program Owner will oversee all aspects of data initiatives, from inception to completion, ensuring projects are delivered on time, within budget, and meet business objectives.

The Data and AI Governance Leader, will play an integral role in orchestrating the governance council and ensuring compliance with governance policies in data, analytics, and AI. Their participation will be instrumental in defining a robust Data and AI Governance Framework, codifying organizational and industry policies into standards, procedures and technical controls ensuring effective, ethical, and legal use of Data & AI technologies