Data Analyst

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.

Title                                : Marketing Analytics Specialist

Experience                   : 5 to 8 yrs

Location                       : Anywhere in India – Preferred Chennai

Type of Hire                  : PwD/Non PwD

Work type                      : Remote

Employment Type      : Full Time

Notice Period               : Immediate

Workday                        : Mon to Fri

Role Overview

We are looking for an experienced Marketing Analytics Specialist to derive actionable commercial insights from Reckitt’s cross-channel e-commerce sales data. The role involves integrating data from multiple, inconsistently structured sources, developing scalable data pipelines and data models, creating business intelligence dashboards, and analyzing the impact of media platform spending on sales performance across various retailer platforms.

Key Responsibilities

• Commercial Analytics: Analyze cross-channel e-commerce sales data to identify trends, performance drivers, and actionable commercial insights.
• Business Requirements: Collaborate with business stakeholders to understand reporting requirements and translate them into analytical solutions.
• Data Architecture: Design and implement efficient data storage, retrieval, and processing architectures.
• ETL Development: Build and maintain robust, scalable ETL pipelines to integrate data from multiple source systems into data warehouses or other storage solutions.
• Data Modelling: Develop and maintain data models aligned with business reporting and analytical requirements.
• Data Quality: Implement data quality checks, validation, and reconciliation processes to ensure data accuracy, completeness, and consistency.
• BI Dashboards & Reporting: Design and develop interactive dashboards and reports that communicate business performance and insights effectively.
• Media Spend Analysis: Analyze the impact of media platform spending on sales performance across multiple retailer platforms and identify opportunities to improve marketing effectiveness.
• End-User Training: Provide training, documentation, and ongoing support to enable business users to use BI tools effectively.

Required Skills

• 5+ years of experience in Marketing Analytics, Data Analytics, Business Intelligence, or a related field.
• Prior hands-on experience in Marketing Analytics, with full proficiency in Claude AI
• Strong SQL skills for data extraction, transformation, and analysis.
• Hands-on experience with ETL/ELT pipelines and data integration from multiple sources.
• Experience with data warehousing concepts and data modeling.
• Proficiency in Power BI, Tableau, or other BI visualization tools.
• Experience analyzing e-commerce sales, marketing performance, media spending, or retailer data.
• Knowledge of data quality, data validation, and reconciliation techniques.
• Strong analytical, problem-solving, and stakeholder communication skills.

Good to Have

• Experience in FMCG, retail, consumer goods, or e-commerce analytics.
• Understanding of digital marketing metrics such as ROI, ROAS, and campaign performance.
• Exposure to marketing attribution or Marketing Mix Modeling (MMM).
• Experience with cloud data warehouses such as Snowflake, BigQuery, Redshift, or Azure Synapse.
• Knowledge of Python or data transformation tools such as dbt.