Research Analyst

We are looking for a detail-oriented and analytical Data Analyst to join our team. The ideal candidate will be responsible for collecting, analyzing, and interpreting data to identify trends, generate insights, and support business decision-making.

The candidate should be comfortable working with large datasets, creating reports and dashboards, and communicating findings clearly to business stakeholders.

Key Responsibilities

• Collect, clean, organize, and analyze data from multiple sources.
• Identify trends, patterns, anomalies, and business opportunities from data.
• Create dashboards, reports, and visualizations for business teams.
• Track and report key performance indicators (KPIs).
• Perform ad-hoc analysis to support business and management decisions.
• Develop and maintain automated reports where possible.
• Work with stakeholders to understand reporting and analytical requirements.
• Ensure data accuracy, consistency, and quality.
• Present analytical findings in a clear and actionable manner.
• Maintain documentation for reports, dashboards, and data processes.

At Nineleaps, we work on bleeding-edge technology with class-leading engineering practices on products that touch the lives of millions of users. We endeavor on doing things the right way, while also promoting a culture of excellence.

About the Role:

We are looking for a Data Analyst with strong analytical and problem-solving skills to transform complex data into meaningful, actionable business insights. The role involves working with large datasets, conducting deep-dive analysis, driving automation, and supporting data-driven product and business decisions.

Key Responsibilities:

• Analyse historical and large datasets to understand data sources, identify trends and patterns, and uncover meaningful insights.
• Write complex SQL queries and leverage Python to perform data analysis, ad hoc investigations, and solve business problems.
• Create reports and translate analytical findings into clear, concise, and actionable recommendations for stakeholders.
• Identify opportunities to drive automation and process improvements, improving efficiency and reducing manual effort.
• Communicate data-driven insights effectively to both technical and non-technical stakeholders in a clear and impactful manner.
• Maintain accurate documentation, ensure high-quality deliverables, and consistently meet defined timelines.

Requirements:

• 3–6 years of experience in Data Analytics, Business Intelligence, Data Engineering, or a similar analytical role.
• Strong hands-on expertise in Python and advanced SQL, with the ability to work with and analyse large datasets.
• Experience working with Google Sheets, and implementing automation through data pipelines or workflows.
• Strong analytical and problem-solving skills, with the ability to interpret complex data and derive actionable insights.
• Excellent communication skills with the ability to effectively present methods, results, and recommendations to stakeholders.
• Ability to collaborate effectively with remote and geographically distributed teams across different time zones.

Company Link: https://www.nineleaps.com/

Company LinkedIn: https://www.linkedin.com/company/nineleaps/

Strong Data Analyst Profile with advanced Excel and SQL expertise

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Mandatory (Experience 1): Must have 4+ years of overall experience as a hands-on Data Analyst

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Mandatory (Tech skill 1): Must be highly proficient in advanced Excel — complex functions, macros, calculations, and pivots

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Mandatory (Tech skill 2): Must have strong hands-on SQL and a good understanding of relational database concepts

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Mandatory (Tech skill 3): Must be able to automate routine tasks using Python (for automation purposes)

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Mandatory (Skill 1): Must have exceptional analytical, problem-solving, and logical skills, with strong attention to detail and accuracy

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Mandatory (Skill 2): Must be able to understand complex data and business logic and convert it into a model (the role models complex utility tariffs, rates, and programs)

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Mandatory (Communication): Must have strong verbal and written communication, able to work independently with India- and US-based team members and articulate problems and solutions over calls and email.

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Mandatory (Location): Must be based locally in Pune (or the nearby Maharashtra belt — Mumbai, Nagpur), as the final round is in person

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Preferred (Domain): Experience in the Energy/Utility industry and familiarity with basic utility (electrical/gas) tariff concepts

We’re looking for a dynamic and driven Data Analyst to join our team of technology enthusiasts. This role is crucial in transforming data into insights that support strategic decision-making and innovation within the insurance technology (InsurTech) space. If you’re passionate about working with data, understanding systems, and delivering value through analytics, we’d love to hear from you.

What We’re Looking For

• Proven experience working as a Data Analyst or in a similar analytical role
• 5+ Years of experience in the field
• Strong command of SQL for querying and manipulating relational databases
• Experience with Power BI for building impactful dashboards and reports
• Familiarity with QlikView and Qlik Sense is a plus
• Ability to communicate findings clearly to technical and non-technical stakeholders
• Knowledge of Python or R for data manipulation is nice to have
• Bachelor’s degree in Computer Science, Statistics, Mathematics, Economics, or a related field
• Understanding of the insurance industry or InsurTech is a strong advantage

What You’ll Be Doing:

• Delivering timely and insightful reports to support strategic decision-making
• Working extensively with Policy Administration System (PAS) data to uncover patterns and trends
• Ensuring data accuracy and consistency across reports and systems
• Collaborating with clients, underwriters, and brokers to translate business needs into data solutions
• Organizing and structuring datasets, contributing to data engineering workflows and pipelines
• Producing analytics to support business development and market strategy

A Market Research Manager in the education sector leads data collection and analysis regarding student demographics, program demand, and competitor positioning. They guide academic program development, enrollment growth, and institutional marketing strategies by turning complex educational data into clear action plans.

Key Responsibilities

• Student & Market Analysis: Study enrollment trends, student behaviour, and shifting demands for online, hybrid, or traditional degree programs.
• Competitor Intelligence: Track competitor institutions, tuition pricing models, course offerings, and scholarship incentives.
• Research Design: Build and run qualitative and quantitative studies, including student surveys, focus groups, and alumni feedback loops.
• Data Reporting: Create visual dashboards, reports, and presentations for academic boards, marketing teams, and university leadership.
• Strategic Advising: Guide program development teams on launch viability and optimal target demographics for new courses or certifications.

Required Qualifications

• Education: Bachelor’s degree in Marketing, Statistics, Economics, Business Analytics, or a related field; master’s or MBA preferred.
• Experience: 4 to 6+ years in market research, with prior exposure to the education, EdTech, or non-profit sector.
• Technical Skills: Proficiency in survey tools (Qualtrics, SurveyMonkey) and data analysis software (SPSS, R, Python, or Excel).
• Soft Skills: Strong verbal communication, stakeholder management, and the ability to explain statistics to non-technical academic leaders.

About the Role

Work at the intersection of business and technology, supporting operations, data analysis, automation, and digital tools to improve efficiency and growth. 

 Responsibilities 

• Support business operations using tech tools (Excel, CRM, dashboards)  
• Analyze data and generate insights for decision-making  
• Assist in automation workflows and process improvements  
• Coordinate between tech and business teams  
• Help in implementing digital solutions and tools  

 Skills Required 

• Basic knowledge of Excel / Google Sheets  
• Good analytical and problem-solving skills  
• Understanding of business processes  
• Interest in technology and automation  

 Details 

• Duration: 3–6 months  
• Mode: Remote  
• Certificate + PPO based on performance 

About VerbaFlo.ai:

VerbaFlo.ai is a fast-growing AI SaaS startup revolutionizing how businesses leverage AI-powered solutions. As a part of our dynamic team, you’ll work alongside industry leaders and visionaries to drive innovation and execution across multiple functions.

Role Overview:

We are seeking a Senior Business Data Analyst with strong experience in analytics, SQL, and dashboarding (preferably Metabase) who can independently lead complex analytical initiatives, translate business problems into scalable data solutions, and mentor junior analysts. This role demands someone who can think strategically, operate with high ownership, and ensure the company runs on accurate, timely, and actionable insights.

Responsibilities:

Strategic & Cross-Functional Ownership

• Partner with leadership (Product, Ops, Growth, Finance) to translate business goals into analytical frameworks, KPIs, and measurable outcomes.
• Influence strategic decisions by providing data-driven recommendations, forecasting, and scenario modeling.
• Drive adoption of data-first practices across teams and proactively identify high-impact opportunity areas.

Analytics & Dashboarding

• Own end-to-end development of dashboards and analytics systems in Metabase (or similar BI tools).
• Build scalable KPI frameworks, business reports, and automated insights to support day-to-day and long-term decision-making.
• Ensure data availability, accuracy, and reliability across reporting layers.

Advanced Data Analysis

• Write, optimize, and review complex SQL queries for deep-dives, cohort analysis, funnel performance, and product/operations diagnostics.
• Conduct root-cause analysis, hypothesis testing, and generate actionable insights with clear recommendations.

Data Infrastructure Collaboration

• Work closely with engineering/data teams to define data requirements, improve data models, and support robust pipelines.
• Identify data quality issues, define fixes, and ensure consistency across systems and sources.

Leadership & Process Excellence

• Mentor junior analysts, review their work, and establish best practices across analytics.
• Standardize reporting processes, create documentation, and improve analytical efficiency.

Core Requirements:

• 5–8 years of experience as a Business Analyst, Data Analyst, Product Analyst, or similar role in a fast-paced environment.
• Strong proficiency in SQL, relational databases, and building scalable dashboards (Metabase preferred)
• Demonstrated experience in converting raw data into structured analysis, insights, and business recommendations.
• Strong understanding of product funnels, operational metrics, and business workflows.
• Ability to communicate complex analytical findings to both technical and non-technical stakeholders.
• Proven track record of independently driving cross-functional initiatives from problem definition to execution.
• Experience with Python, Git, or BI tools like Looker/Power BI/Tableau.
• Hands-on with data warehouses (BigQuery, Redshift, Snowflake).
• Familiarity with product analytics tools (Mixpanel, GA4, Amplitude).
• Exposure to forecasting, financial modeling, or experimentation (A/B testing).

Why Join Us?

• Work directly with top leadership in a high-impact role.
• Be part of an innovative and fast-growing AI startup.
• Opportunity to take ownership of key projects and drive efficiency.
• A collaborative, ambitious, and fast-paced work environment.
• Perks & Benefits: gym membership benefit, workation policy, and company-sponsored lunch.

If you’re looking for an exciting role that combines strategy, execution, and leadership exposure, we’d love to hear from you!

Apply now to join VerbaFlo.AI on this journey.

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.

Key Responsibilities

 Strong understanding of Machine Learning algorithms (supervised and unsupervised)

 Hands-on experience with Deep Learning frameworks (TensorFlow, PyTorch, or similar)

 Experience in NLP techniques and libraries (NLTK, spaCy, Hugging Face, etc.)

 Solid knowledge of Statistics, probability, and data analysis methods

 Proficiency in SQL for querying relational databases

 Strong programming skills in Python (or similar languages)

 Excellent communication skills with the ability to explain complex concepts simply

Required Qualifications

 3+ years of hands-on experience as a Data Scientist or in a similar role.

 Strong expertise in classical machine learning and regression modeling.

 Solid understanding of statistics, including probability, distributions, hypothesis testing,

and correlation analysis.

 Proficiency in Python with libraries such as: scikit-learn pandas NumPy

 Experience working with structured/tabular data.

 Strong problem-solving and analytical thinking skills.

 Ability to clearly explain models and results to non-technical stakeholders.

This role will be permanent with NAM info and deploy to client location Hyderabad & Pune.

Work Mode: WORK FROM OFFICE

Role Descriptions:

• Perform detailed data analysis and support business decision-making
• Gather and document business requirements and translate them into technical specifications
• Work closely with stakeholders to define data needs and reporting requirements
• Create user stories, functional specifications, and support UAT activities
• Ensure alignment between business objectives and data solutions

Required Skills:

• Strong expertise in SQL and data querying
• Proven experience in data analysis, requirement gathering, and stakeholder management
• Ability to translate business requirements into technical solutions and user stories
• Good understanding of data models, reporting, and analytics concepts

Skills: Business Analysis~ORACLE SQL

Locations: ~HYDERABAD~PUNE~

Desire candidate

• Candidate should have valid PF.