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150
K
Top-rated, highly skilled global talent pool
$
80,000
Cost savings per talent hired through Andela
66
%
Faster time to hire
33
%
Faster project delivery
Tech leaders trust Andela to quickly source qualified talent
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Experienced Professionals Are Ready To Get Started On Your Next Data Analytics Project
The Andela Standard: Network Entrance Assessments
Successful Data Analysts exhibit proficiency in data analysis tools, demonstrate a deep understanding of data architecture, and showcase problem-solving abilities in dynamic data environments.
1. Qualifications
Qualification criteria:
- A minimum of 4 years of professional experience in a Data Analysis role (excluding intern and volunteer experience).
- A bachelor's degree in a technology-related field or equivalent work experience.
- Excellent spoken and written English communication skills.
- Proficient in data analysis tools with a solid understanding of data analysis principles.
- Hands-on experience with data-related technologies, including databases, querying languages, and statistical analysis tools.
- Strong problem-solving skills, attention to detail, and a results-oriented mindset.
- A commitment to continuous learning and adapting to evolving data technologies.A collaborative and team-oriented approach to data analysis projects.
2. Skill Validation
This qualification assessment tests the candidate's knowledge of Data Analysis fundamentals. It's composed of Q&A and code challenges that evaluate theoretical knowledge and hands-on skills.A techoloigst’s is approved in this test if all challenge level cut-off scores are met.
Data Analysis
This challenge evaluates knowledge of Data Analysis concepts and practices, focused on real-world, typical use cases of the data analisis discipline. It covers data modeling, BI concepts, and data visualizations. Most questions are derived from data analysis certifications and some inspired by frequent data analysis interview questions.
SQL
This challenge tests knowledge of SQL and associated best practices. Question difficulty ranges from basic to intermediate, so the challenge should be suitable for any experienced SQL practioner. Most of the questions are derived from SQL certifications and some inspired by frequent SQL interview questions.
SQL Code Challenge
This challenge tests basic ability to utilize aggregation, JOIN and GROUP BY features. This is a straightforward challenge that is meant to evaluate specific SQL language feature knowledge.
3. Technical Interview
This assessment evaluates the expertise in Data Analysis through a real-time challenge. It's designed to be used as an interactive session with the technical screener.
During the assessment, technologists will tackle a hands-on problem tailored real-world scenario in SQL query development. Their solution will be first verified by a battery of automated test cases to ensure it meets the functional requirements as well as industry standards. Then, our experienced interviewers step in to assess the overall efficiency of the technologist's solution.
Assessment Outline:
- Data Analysis Coding Challenge (Pandas):
- This is an intermediate-to-advanced-level problem that tests skills in data analysis using a programmatic approach. The task is to load files in CSV format, and process the data using Pandas dataframes.
- Data Analysis Coding Challenge (SQL):
- This is an intermediate-to-advanced-level problem that tests skills in data analysis using relational databases. The task is to process the data using SQL.
Anurag P.
Data Scientist
Experience:
10+ years
Availability:
Full-time
Anurag is an inquisitive Data Scientist with 8+ years of professional experience uncovering complex problems and implementing innovative solutions through advanced analytics and Machine Learning. He is proficient in Python, R, BigQuery, SQL, Looker, Keras, TensorFlow, and Tableau. Anurag possesses a deep understanding of time series forecasting, random forest, Lasso regression, and XGBoost.
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Omotayo I.
Data Analyst
Experience:
10+ years
Availability:
Full-time
Seasoned Data professional with 8+ years' expertise in statistical modeling, data automation, and impactful dashboard creation. Skilled in Python, R, SQL, and BigQuery, I specialize in microfinance, leveraging A/B testing, quantitative research, and statistical computing to address complex challenges. Proven success in developing credit scoring models, client churn predictions, and accurate forecasting solutions.
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Allan S.
Data Engineer
Experience:
6 years
Availability:
Full-time
Allan is a highly proficient and dedicated Senior Data/Analytics Engineer with expertise in data collection, processing, and advanced data modeling using dbt, and orchestration with Airflow & Prefect. He excels in dynamic dashboard development, particularly with Tableau, Powerbi, Looker and Metabase empowering stakeholders to make informed decisions.
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Expert in
Avinash N.
Data Scientist
Experience:
9 years
Availability:
Full-time
Avinash is a seasoned Data Scientist, Machine Learning Engineer, Gen Ai Scientist - with almost a decade of proven expertise in LLM, Langchain, Generative Ai, data analysis, predictive modeling, and business intelligence. His proficiency extends to cutting-edge technologies such as Generative Ai, LLM, Deep Learning, neural networks, natural language processing (NLP), TensorFlow, and Keras. He excels in Python, Snowflake, AWS, SQL, Machine Learning, and statistical modeling, Project Management, decision-making through data-driven strategies
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Expert in
Emmanuel D.
Full-Stack Engineer
Experience:
6 years
Availability:
Full-time
Emmanuel is a seasoned Full-Stack Engineer, boasting over 6 years of experience crafting user-friendly web applications and essential business API services. His expertise spans a wide array of technologies, including JavaScript, Node.js, HTML/CSS, React Native, Vue.js, React, PHP, PostgreSQL, and more.
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Expert in
MySQL
JavaScript
Node.js
React.js
TypeScript
Git
Heroku
HTML
Redis
Get all your initiatives back on the table
Back-End
Python
Back-End
Python
Back-End
Python
Back-End
Python
Front-End
React
Front-End
React
Front-End
React
Front-End
React
Data
R
Data
R
Data
R
Data
R
Mobile
Android
Mobile
Android
Mobile
Android
Mobile
Android
Back-End
Java
Back-End
Java
Back-End
Java
Back-End
Java
Front-End
JavaScript
Front-End
JavaScript
Front-End
JavaScript
Front-End
JavaScript
Data
TensorFlow
Data
TensorFlow
Data
TensorFlow
Data
TensorFlow
Mobile
iOS
Mobile
iOS
Mobile
iOS
Mobile
iOS
Back-End
Go
Back-End
Go
Back-End
Go
Back-End
Go
Data
Excel
Data
Excel
Data
Excel
Data
Excel
Front-End
Node.js
Front-End
Node.js
Front-End
Node.js
Front-End
Node.js
Front-end
CSS
Front-end
CSS
Front-end
CSS
Front-end
CSS
Data
SQL
Data
SQL
Data
SQL
Data
SQL
Data
Apache
Data
Apache
Data
Apache
Data
Apache
Back-End
C#
Back-End
C#
Back-End
C#
Back-End
C#
Front-End
Typescript
Front-End
Typescript
Front-End
Typescript
Front-End
Typescript
Data
PyTorch
Data
PyTorch
Data
PyTorch
Data
PyTorch
Front-End
HTML
Front-End
HTML
Front-End
HTML
Front-End
HTML
Back-End
Ruby
Back-End
Ruby
Back-End
Ruby
Back-End
Ruby
Back-End
PHP
Back-End
PHP
Back-End
PHP
Back-End
PHP
Work the way that
works for you
Andela’s Adaptive Hiring approach offers a flexible engagement model that lets you create and manage teams in any configuration.
Hire Individuals
Fill a critical gap or place a highly skilled problem solver. Have someone cover maternity leave. Or put a full-time, project-driven technologist in place.
Create Managed Projects
We ensure on time, on budget delivery for the most demanding projects, like custom application development and AI rapid prototyping.
Frequently Asked Questions
Where can I hire Data Analysts?
Andela is a premier global talent marketplace that connects companies with highly skilled Data Analysts from around the world. With a rigorous certification process and focus on quality talent, Andela provides access to a diverse pool of experienced Data professionals ready to join your team.
How are Andela Data Analysts different?
Andela Data Analysts stand out for their exceptional technical skills, work ethic, and cultural fit. Through an AI-driven platform, rigorous certification process, and professional matchers, Andela ensures companies are connected to highly skilled professionals who are not only proficient in Data Analysis but also possess strong problem-solving abilities, excellent communication skills, and a passion for continuous learning. Andela’s developers are also trained in remote collaboration and agile methodologies, enabling seamless integration into your team.
How long does it take to hire Data Analysts through Andela?
Andela’s streamlined hiring process ensures you can access top Data Analysts quickly. Once you submit your hiring request, Andela typically provides you with a curated list of pre-qualified candidates within seconds and you can hire within 48 hours - after conducting interviews and making a decision. With Andela’s global talent pool, you can scale your Data Analytics team rapidly, without compromising on quality.
What are the minimum requirements of all Andela Data Analysts?
- A minimum of 4 years of professional experience in a Data Analysis role (excluding intern and volunteer experience).
- A bachelor's degree in a technology-related field or equivalent work experience.
- Excellent spoken and written English communication skills.
- Proficient in data analysis tools with a solid understanding of data analysis principles.
- Hands-on experience with data-related technologies, including databases, querying languages, and statistical analysis tools.
- Strong problem-solving skills, attention to detail, and a results-oriented mindset.
- A commitment to continuous learning and adapting to evolving data technologies.A collaborative and team-oriented approach to data analysis projects.
What are the typical responsibilities of a Data Analyst?
- Analyze, interpret, and maintain scalable and efficient data analysis processes using various tools and technologies.
- Collaborate with cross-functional teams to ensure the seamless integration of data analysis components into the overall analytical architecture.
- Optimize data analysis performance, ensuring accurate and efficient insights extraction.
- Troubleshoot and resolve data-related issues, identifying and implementing effective solutions for seamless data analysis.
- Participate actively in code reviews to uphold coding standards, improve code quality, and advocate for best practices in data analysis.
- Stay abreast of the latest trends, updates, and best practices in data analysis and related technologies.
- Provide mentorship and guidance to junior data analysts, sharing insights and expertise in data analysis principles and practices.
What skills should a Data Analyst possess?
Data Analysts play a key role in analyzing, enhancing, and interpreting data to provide valuable insights. Collaborating cross-functionally, they ensure effective data integration, optimize analytical performance, and tackle intricate data-related challenges. Successful Data Analysts should exhibit proficiency in data analysis tools, demonstrate a deep understanding of data architecture, and showcase problem-solving abilities in dynamic data environments.
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