As a Product Analyst at Apna, you will play a crucial role in shaping the future of the platform through data-driven decision making. You will leverage your technical skills to solve complex problems across different business verticals, design and execute experiments, and communicate insights to stakeholders. This role offers the freedom to create and execute a compelling vision and roadmap to power business decisions through advanced analytics solutions.
Apna is a leading job search platform in India, dedicated to helping users find employment opportunities that match their skills and interests. With a strong focus on community building and job matching, Apna has become a go-to platform for job seekers and employers alike. The company's mission is to empower people to find better job opportunities and uplevel their lives in meaningful ways.
Why required: SQL is required to manage and analyze large datasets, which is critical for making data-driven decisions in product analytics.
How recruiters evaluate: The recruiter will evaluate your ability to write efficient SQL queries, manage databases, and perform data analysis.
Why required: Python is a popular programming language used in data science and analytics. It is required for data analysis, machine learning, and experimentation.
How recruiters evaluate: The recruiter will evaluate your ability to write Python code, work with popular libraries like Pandas and NumPy, and perform data analysis.
Why required: R is a programming language used for statistical computing and graphics. It is required for data analysis, machine learning, and experimentation.
How recruiters evaluate: The recruiter will evaluate your ability to write R code, work with popular libraries like dplyr and tidyr, and perform data analysis.
Why required: A/B testing is a crucial aspect of product analytics, and it requires a strong understanding of statistics and experimentation.
How recruiters evaluate: The recruiter will evaluate your ability to design and execute A/B tests, analyze results, and communicate insights.
Why required: Multivariate testing is an advanced form of A/B testing that requires a strong understanding of statistics and experimentation.
How recruiters evaluate: The recruiter will evaluate your ability to design and execute multivariate tests, analyze results, and communicate insights.
Why required: Design of experiments is a crucial aspect of product analytics, and it requires a strong understanding of statistics and experimentation.
How recruiters evaluate: The recruiter will evaluate your ability to design and execute experiments, analyze results, and communicate insights.
Why required: Statistics is a fundamental aspect of product analytics, and it requires a strong understanding of statistical concepts and techniques.
How recruiters evaluate: The recruiter will evaluate your ability to apply statistical concepts to real-world problems, analyze data, and communicate insights.
Why required: Machine learning is a crucial aspect of product analytics, and it requires a strong understanding of machine learning concepts and techniques.
How recruiters evaluate: The recruiter will evaluate your ability to apply machine learning concepts to real-world problems, analyze data, and communicate insights.
Why required: Research methods are essential in product analytics, and they require a strong understanding of research design, data collection, and data analysis.
How recruiters evaluate: The recruiter will evaluate your ability to design and execute research studies, analyze data, and communicate insights.
Freshers with a strong background in statistics, machine learning, and programming languages like Python or R can apply.
Experienced professionals with a background in product analytics, data science, or a related field can apply.
Graduates with a degree in statistics, mathematics, computer science, or a related field can apply.
B.Tech graduates with a degree in computer science, information technology, or a related field can apply.
MCA graduates with a degree in computer applications or a related field can apply.
Diploma holders with a degree in computer science, information technology, or a related field can apply.
The average salary for a Product Analyst in India is around ₹12-15 lakhs per annum.
Freshers can expect a salary range of ₹8-12 lakhs per annum.
Experienced professionals can expect a salary range of ₹15-25 lakhs per annum.
The salary range can vary based on factors like location, experience, and company size.
A Senior Product Analyst will lead the product analytics team and be responsible for making strategic decisions.
A Product Manager will be responsible for leading the product development team and making strategic decisions.
A Data Scientist will be responsible for developing and implementing machine learning models and algorithms.
This course will help you develop a strong background in statistics and machine learning.
This course will help you develop a strong background in Python programming.
This course will help you develop a strong background in data analysis and visualization.
To succeed in this role, you need to have a strong background in statistics, machine learning, and programming languages like Python or R. You should also have experience in product analytics, data science, or a related field.
The text below is preserved from the employer's listing for verification. CampusToCareer editorial content above is the primary guide for preparing your application.
About the job
About the role:
Apna Advantage team is looking for someone enthusiastic about product analytics and
experimentation who will join us and shape the future of our apna platform. You will leverage your
strong technical skills to solve problems across different business verticals at apna in a data-driven
way. This role comes with the freedom of creating and executing a compelling vision and roadmap to
power our business decisions through advanced analytics solutions, A/B testing, offline evaluation,
and exploration capabilities. You will manage the quality of decisions taken based on the results of
these advanced analyses, which would imply supporting experimentation design, data analysis, and
communication of the results.
The role also involves working closely with business leaders to ensure meaningful and actionable
insights on current tests and analyses, and you will partner with the data science team to stand up
advanced experimentation methods for long-term, scalable improvements in the ML solutions that
we build.
We are a group of highly talented folks with end-to-end expertise in bringing data products to life. You
will have an opportunity to define and shape the future of jobs and community products at apna. Your
work will impact billions across the world and help them find the jobs that uplevel their lives in
meaningful ways.
Requirements
What will you do:
Define and monitor key performance metrics to ensure product success and take a data-driven approach to create and iterate on the product
Conduct complex statistical analyses to uncover key drivers of the business
Conduct test design, measurement of A/B & Multivariate tests across several testing
programs
Utilize standard t-tests, advanced analytical techniques, and existing data science models to generate insights from tests and analyses
Provide feedback to product and engineering teams on the impact of the new product launches: target launch metrics, A/B testing, post-launch metrics
Present data analysis and product performance evaluations to stakeholders and cross-functional teams
Learn and adopt new tools & technologies for advanced analytics and experimentation
Foster a shared purpose and collaborative learning environment among team members that enhances the capabilities of the team
Must have:
1-3 years of work experience in analytics
1+ years of experience developing statistical solutions in areas such as A/B and multivariate testing, causal inferences, and design of experiments
Strong coding skills in SQL
Strong problem-solving skills and ability to synthesize actionable insights and strategies from complex data
Excellent communication and stakeholder management skills
Good to have:
Experience with statistical programming languages such as Python or R
Significant experience, proficiency in, and passion for Mobile and/or Web product
Direct experience in the experimentation area
Proven analytical skills and deep understanding of statistics, machine learning, and
research methods
Experience communicating with stakeholders, including product managers, data scientists and engineers
Experience working on product analytics tools like Mixpanel or Amplitude equivalent
