Data Engineer - Python at Rudhra Info Solutions · Bengaluru (Bangalore), Chennai · 5 - 6 years · ₹7L - ₹15L / yr · Profitable · Posted 6 Jul 2022
- Analyze and organize raw data
- Build data systems and pipelines
- Evaluate business needs and objectives
- Interpret trends and patterns
- Conduct complex data analysis and report on results
- Build algorithms and prototypes
- Combine raw information from different sources
- Explore ways to enhance data quality and reliability
- Identify opportunities for data acquisition
- Should have experience in Python, Django Micro Service Senior developer with Financial Services/Investment Banking background.
- Develop analytical tools and programs
- Collaborate with data scientists and architects on several projects
- Should have 5+ years of experience as a data engineer or in a similar role
- Technical expertise with data models, data mining, and segmentation techniques
- Should have experience programming languages such as Python
- Hands-on experience with SQL database design
- Great numerical and analytical skills
- Degree in Computer Science, IT, or similar field; a Master’s is a plus
- Data engineering certification (e.g. IBM Certified Data Engineer) is a plus

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Job Title: Senior Data Analyst
Location: Sharnam Metrolinks, Amraiwadi, Ahmedabad
Working Days: 6 Days a Week
Department: MDO
Reporting To: COO
Employment Type: Full-Time
Job Summary
We are seeking a highly analytical and detail-oriented Senior Data Analyst to lead data management, reporting, automation, and system development initiatives across the organization.
The role focuses on transforming raw data into meaningful insights, designing and implementing automated systems, strengthening data structures, and supporting cross-functional teams with accurate, actionable intelligence to drive strategic and operational business decisions.
Key Responsibilities
1. Data Management & Reporting
● Collect, clean, validate, and consolidate data from multiple internal and external sources.
● Prepare and deliver daily, weekly, and monthly MIS reports for management and departments.
● Design, develop, and maintain dashboards to track KPIs, performance metrics, and operational trends.
2. Database & Data Accuracy Management
● Manage and regularly update internal databases, spreadsheets, and reporting systems.
● Ensure data accuracy, consistency, integrity, and confidentiality across all platforms.
● Implement best practices for data validation, version control, and audit checks.
3. Data Analysis & Business Insights
● Analyze large and complex datasets to identify trends, patterns, gaps, and anomalies.
● Translate data findings into clear, actionable insights and recommendations to support
strategic and operational decision-making.
4. Reporting Automation, System Recommendation & Implementation
● Identify opportunities to replace manual or semi-manual processes with automated, data-driven systems.
● Design and implement automated reporting frameworks, dashboards, and data pipelines using Excel (Power Query, VBA, Macros), SQL, BI tools, and Python.
● Proactively suggest new automation tools, system enhancements, or integrations to
improve efficiency, accuracy, and scalability.
● Lead the end-to-end implementation of approved automation initiatives, including requirement gathering, system design, testing, deployment, and stabilization.
● Continuously monitor and optimize automated systems in line with business growth and evolving data needs.
5. Cross-Functional Coordination & Support
● Collaborate with Sales, HR, Finance, Operations, and other departments to understand
reporting and data requirements.
● Provide support for ad-hoc analysis, custom reports, and special data requests.
● Act as a data partner to department heads for decision support and performance tracking.
6. Documentation & Compliance
● Maintain complete and updated documentation for MIS processes, reports, data models,
automation logic, and system changes.
● Ensure compliance with company data governance policies and applicable data protection standards.
System Development & Data Structuring Responsibilities
● Study and understand departmental workflows to evaluate how data is generated, processed, and utilized.
● Review existing manual and digital data systems to identify operational gaps, risks, and
mprovement opportunities.
● Recommend structured data models, reporting formats, and storage solutions aligned with
business requirements.
● Coordinate with department heads to define data structures, access levels, and reporting
standards.
● Implement new or upgraded data systems (Excel-based models, cloud platforms, ERP
integrations) with minimal operational disruption.
● Design structured data formats and role-based access controls to ensure secure and
organized data management.
● Train employees on newly implemented systems and provide post-implementation
support.
● Monitor system performance, resolve issues, and continuously improve systems based on
user feedback and organizational growth.
Qualifications & Experience
● Bachelor’s degree in Commerce, Statistics, Computer Applications, or a related field.
● 3–5 years of experience in data analytics, reporting, or system automation roles.
● Strong analytical thinking, logical reasoning, and problem-solving abilities.
● High attention to detail with excellent organizational and documentation skills.
Technical Skills (Must Have)
● Advanced Excel: Power Query, Power Pivot, VBA basics, Macros, Charts
● BI Tools: Power BI or Tableau (DAX, data modeling, dashboard optimization)
● Google Apps Script: Automation in Google Sheets, custom functions, triggers, API integrations, workflow optimization
● Vlook
Preferred Skills
● Strong verbal and written communication skills
● Ability to handle sensitive and confidential information responsibly
● Quick learner with a tech-savvy, improvement-driven, and solution-oriented mindset
Job Description:
As a Data Science Intern, you will collaborate with our data science and analytics teams to work on meaningful projects involving data analysis, predictive modeling, and statistical modeling. You will have the opportunity to apply your academic knowledge in a practical, fast-paced environment, contribute to key data-driven projects, and gain valuable experience with industry-leading tools and technologies.
Responsibilities:
- Assist in collecting, cleaning, and preprocessing data from various sources.
- Perform exploratory data analysis to identify trends, patterns, and anomalies.
- Develop and implement machine learning models and algorithms.
- Create data visualizations and reports to communicate findings to stakeholders.
- Collaborate with team members on data-driven projects and research.
- Participate in meetings and contribute to discussions on project progress and strategy.
- Work with large datasets to clean, preprocess, and analyze data.
- Build and deploy statistical and machine learning models to generate actionable insights.
- Conduct exploratory data analysis (EDA) to uncover trends, patterns, and correlations.
- Assist in the creation of data visualizations and dashboards for reporting insights.
- Support the development and improvement of data pipelines and algorithms.
- Collaborate with cross-functional teams to understand data needs and translate them into actionable analytics solutions.
- Contribute to the documentation and presentation of results, findings, and recommendations.
- Participate in team meetings, brainstorming sessions, and project discussions.
Duration: 03 Months (with the possibility of extending up to 6 months)
MODE: Work From Home (Online)
Requirements:
- Any Graduate / PassOuts / Freasher can apply.
- Currently pursuing a Bachelor's or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.
- Proficiency in programming languages such as Python, R, or SQL.
- Strong foundation in statistics, probability, and data analysis techniques.
Benefits
Internship Certificate
Letter of recommendation
Stipend Performance Based
Part time work from home (2-3 Hrs per day)
5 days a week, Fully Flexible Shift
About Us
Corporate Web Solutions works on technology-driven digital solutions involving data, automation, web technologies, and artificial intelligence. Our internship programs focus on practical learning and real-world project exposure.
Role Overview
As a Data Science Intern, you'll work with datasets to perform analysis, visualization, and machine learning tasks while learning modern AI-assisted workflows.
Key Responsibilities
- Collect, clean, and analyze datasets.
- Perform exploratory data analysis.
- Create data visualizations and reports.
- Assist in developing machine learning models.
- Work with Python-based data science tools.
- Explore AI tools for data analysis and productivity.
Requirements
- Basic knowledge of Python.
- Understanding of data analysis fundamentals.
- Familiarity with Pandas and NumPy is a plus.
- Basic understanding of statistics.
- Analytical and problem-solving skills.
Perks
- Certificate of Internship
- Flexible work hours
- Mentorship and real project exposure
- Potential for PPO
- Letter of Recommendation
- Performance-Based Stipend available up to ₹18,000/month
About the Company:
WebMD Health Corp., an Internet Brands Company, is the leading provider of health information services, serving patients, physicians, health care professionals, employers, and health plans through our public and private online portals, mobile platforms, and health-focused publications. The WebMD Health Network includes WebMD Health, Medscape, Jobson Healthcare Information, prIME Oncology, MediQuality, Frontline, QxMD, Vitals Consumer Services, MedicineNet, eMedicineHealth, RxList, OnHealth, Medscape Education, and other owned WebMD sites. WebMD®, Medscape®, CME Circle®, Medpulse®, eMedicine®, MedicineNet®, theheart.org®, and RxList® are among the trademarks of WebMD Health Corp. or its subsidiaries. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.
For Company details, visit our website: www.webmd.com
Experience: 3+ years
Qualification: Master's degree in Computer Science, Statistics, Mathematics, or a related field.
Work Timings: 2 PM to 11 PM IST
Position Requirement:
- Write clean and efficient code in Python and/or R for data analysis, statistical modeling, and machine learning tasks.
- Apply statistical and machine learning techniques to analyze large datasets and extract meaningful patterns, trends, and insights. Develop and implement predictive models for various business applications.
- Formulate hypothesis tests and design experiments to validate assumptions, measure the impact of changes, and optimize decision-making processes.
- Demonstrate strong SQL skills for efficient data querying and manipulation using window functions.
- Work with large datasets and ensure data quality and accuracy.
- Experience with dashboarding tools like Tableau is a plus to visualize and present data-driven insights to both technical and non-technical stakeholders.
- Ability to communicate complex technical concepts and insights in a clear and concise manner to both technical and non-technical audiences. Engage with the leadership team and clients to understand business requirements and provide data-driven solutions.
- Work with real world case studies in Data Science and a chance to implement various modelling techniques. Opportunity to independently execute and lead analytical projects and assignments.
- Help solve some challenging Healthcare related digital marketing problems globally. Transform business question into data requirements; collect and merge the data; analyse the data, link it to the business reality and present the results
- Develop predictive models and machine learning algorithms to study change in physician prescribing behaviour as well as WebMD integrated campaign response behaviour. Build analysis to understand user engagement and behaviours across various WebMD products.
Technical Skills needed:
1.Experience with data manipulation in SQL environment is a must. Experience with BigQuery/Vertica data warehousing is good to have
- Experience with statistical and data manipulation tools such as Python or R is a must
- Need very good expertise in using Microsoft Excel, and Microsoft PowerPoint. Excellent presentation skills required
- Experience developing statistical models like hypothesis testing, regression models, classifications models, forecasting etc is a must
- Algorithm designing and implementation skills in R or Python is required
Requirements
- B.Tech/B.E. / MSc Statistics from premier institutes with
- Minimum 80% marks in 10th and 12th
- Minimum 75% marks in graduation
- 2-5 years of relevant work experience in analytics field
- Proven experience in data science, statistical modeling, and machine learning applications.
- Strong proficiency in Python and/or R programming languages.
- Solid understanding of statistical concepts, hypothesis testing, and experimental design
- Expertise in SQL for data querying and manipulation.
- Familiarity with dashboarding tools is a plus.
- Excellent presentation, communication and interpersonal skills.
About Us
Corporate Web Solutions provides technology-driven solutions involving data analysis, automation, web development, and digital transformation.
Role Overview
As a Data Analyst Intern, you'll assist in analyzing datasets, preparing reports, identifying trends, and exploring AI-assisted analytics workflows.
Key Responsibilities
- Collect and organize data.
- Analyze datasets and identify trends.
- Prepare reports and visualizations.
- Work with Excel, spreadsheets, or analytical tools.
- Assist with dashboards and data-driven insights.
- Explore AI tools for data analysis.
Requirements
- Basic understanding of data analysis.
- Familiarity with Excel or Google Sheets.
- Basic knowledge of SQL or Python is a plus.
- Analytical mindset.
- Good attention to detail.
Perks
- Certificate of Internship
- Flexible work hours
- Mentorship and real project exposure
- Potential for PPO
- Letter of Recommendation
- Performance-Based Stipend available up to ₹18,000/month
About the Role
We are looking for enthusiastic Data Analytics Interns to join our team remotely for a 3-month internship. This is an excellent opportunity to gain hands-on experience in data analysis, data visualization, database management, and reporting. The selected candidates will have the opportunity to work on real projects, analyze datasets, and develop their technical and analytical skills.
Responsibilities
- Assist in collecting, cleaning, organizing, and analyzing datasets.
- Work with SQL and databases for data retrieval, manipulation, and analysis.
- Use Microsoft Excel to organize data, perform calculations, and prepare reports.
- Assist in creating dashboards and visualizations using Power BI or Tableau.
- Work with Python libraries such as Pandas and NumPy for data analysis.
- Perform exploratory data analysis to identify trends, patterns, and insights.
- Prepare reports and presentations based on analytical findings.
- Assist in tracking key performance indicators (KPIs) and monitoring business data.
- Maintain accurate documentation of data analysis activities and project contributions.
- Collaborate with team members on data-related projects and analytical tasks.
Requirements
- Basic knowledge of Data Analytics and data analysis concepts.
- Understanding of SQL and database fundamentals.
- Familiarity with Microsoft Excel and data management.
- Basic knowledge of Python is preferred.
- Familiarity with data visualization tools such as Power BI or Tableau is an advantage.
- Strong analytical and problem-solving skills.
- Good research and organizational abilities.
- Attention to detail and accuracy.
- Ability to work independently in a remote environment.
- Good communication skills and eagerness to learn.
What You'll Gain
- Real-world experience in data analytics and business intelligence.
- Hands-on experience with data cleaning, analysis, and visualization.
- Exposure to industry-relevant tools such as SQL, Python, Excel, and Power BI.
- Mentorship and exposure to practical analytical processes.
- Completion Certificate at the end of the internship.
- Letter of Recommendation based on performance.
- Opportunity to strengthen your portfolio with real-world data projects.
Internship Details
- Duration: 3 months
- Location: Remote (Work from Home)
- Perks: Completion Certificate + Letter of Recommendation
Job Title: Data Intern
Company: Honeybee Digital
Location: Remote
Internship Duration: 3 Months
Job Type: Internship
Working Hours
- Full-time: 9:00 AM – 6:00 PM
- Part-time: 9:00 AM – 1:00 PM / 1:00 PM – 6:00 PM
About the Role
We are looking for a detail-oriented and analytical Data Intern who is eager to work with data and gain hands-on experience in data management, analysis, and reporting. This role is ideal for candidates interested in building a career in data analysis, business intelligence, or data science.
Key Responsibilities
- Collect, organize, and maintain data from various sources
- Clean and preprocess data to ensure accuracy and consistency
- Assist in data analysis and generate basic insights
- Create reports and dashboards using tools like Excel or Google Sheets
- Support teams with data requirements for marketing, operations, and business decisions
- Perform data entry and validation tasks
- Identify patterns, trends, and anomalies in datasets
- Maintain proper documentation of data processes
Requirements
- Basic knowledge of Excel / Google Sheets
- Understanding of data handling and analysis concepts
- Attention to detail and accuracy
- Basic problem-solving and analytical thinking skills
- Familiarity with tools like Python, SQL (optional but preferred)
- Ability to manage tasks and meet deadlines
- Willingness to learn and work with data
Skills You Will Gain
- Hands-on experience in data collection, cleaning, and analysis
- Exposure to real-world datasets and reporting
- Practical knowledge of Excel, data visualization, and analytics tools
- Understanding of business decision-making using data
- Experience working in a professional environment
Who Can Apply
- Students pursuing Data Science, Computer Science, IT, Statistics, or related fields
- Freshers interested in data analysis and data-related roles
- Candidates looking to gain practical experience in data handling and analytics
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Job Summary:
We are looking for a skilled Data Scientist with strong expertise in demand forecasting, predictive analytics, and emerging Generative AI technologies. The ideal candidate should have hands-on experience in machine learning, deep learning, NLP, and LLM-based solutions, along with proficiency in Python, SQL, Power BI, and advanced Excel. This role involves building scalable forecasting models and leveraging AI/GenAI to deliver actionable business insights.
Key Responsibilities:
- Develop and deploy demand forecasting models using machine learning and deep learning techniques.
- Analyze historical data to identify trends, seasonality, and demand patterns.
- Build predictive models to improve supply chain and inventory planning.
- Work with large datasets using Python and SQL for data extraction, transformation, and analysis.
- Design dashboards and reports using Power BI for business stakeholders.
- Utilize advanced Excel techniques (Pivot Tables, Power Query, formulas) for analysis and reporting.
- Build and integrate NLP-based solutions for text data analysis and insights.
- Develop and implement LLM-based applications using Generative AI frameworks.
- Design and deploy RAG (Retrieval-Augmented Generation) pipelines for intelligent data retrieval and response generation.
- Collaborate with cross-functional teams (operations, finance, product) to align forecasting and AI solutions.
- Continuously improve model accuracy and performance through experimentation and optimization.
Required Skills:
- Strong proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch).
- Solid understanding of machine learning & deep learning algorithms.
- Experience in demand forecasting / time-series analysis (ARIMA, Prophet, LSTM, etc.).
- Hands-on experience with NLP techniques and libraries (NLTK, SpaCy, Transformers).
- Experience working with LLMs and Generative AI frameworks (OpenAI, Hugging Face, LangChain, etc.).
- Strong understanding of RAG architectures and vector databases (FAISS, Pinecone, etc.).
- Advanced knowledge of SQL for data manipulation.
- Hands-on experience with Power BI for visualization and reporting.
- Expertise in advanced Excel (Power Query, dashboards, data modeling).
- Strong analytical and problem-solving skills.
Preferred Qualifications:
- Experience in supply chain, logistics, or e-commerce forecasting.
- Knowledge of cloud platforms (AWS, Azure, or GCP).
- Familiarity with data pipelines and ETL processes.
- Understanding of business metrics and KPIs related to demand planning.
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.












