11 answers
Jane
Student
Alaska, MI
1
Question
Asked
1316 views
How do I find a mentor and begin my interest in Data analysis ?
I am a college student studying applied mathematics but I have interest in Data analysis. I will love to know how I can combine the two together without it affecting my studies .
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11 answers
Trey Hensel
Quantitative Analyst
1
Answer
Fairfield, Connecticut
Updated
Trey’s Answer
Hi Jane,
I would recommend reaching out to your professors that work in the intersection of applied mathematics and data science, especially if you're currently taking their course. I found it to be very helpful to ask questions to my professors after lectures and/or attend their office hours. This shows your professors that you have genuine interest in their work/projects and allows you to build a meaningful connection. Even if your professor's work is not exactly what you're interested in, you always have them connect you with another faculty member that is more aligned with your interests. This is just one path you can take, but in my experience, this has been the most effective way to learn more about topics you may be interested in.
I would recommend reaching out to your professors that work in the intersection of applied mathematics and data science, especially if you're currently taking their course. I found it to be very helpful to ask questions to my professors after lectures and/or attend their office hours. This shows your professors that you have genuine interest in their work/projects and allows you to build a meaningful connection. Even if your professor's work is not exactly what you're interested in, you always have them connect you with another faculty member that is more aligned with your interests. This is just one path you can take, but in my experience, this has been the most effective way to learn more about topics you may be interested in.
Sarah Halil
IT Quality Analyst
6
Answers
Tampa, Florida
Updated
Sarah’s Answer
Hello Jane,
Your question has sparked an engaging conversation with insightful responses. It's fantastic that you're still in college because this offers you a multitude of options. You have a valuable network right within your school.
I strongly recommend that you engage with your college counselor and professors. They are a full of knowledge and experience, ready to guide you.
Don't miss out on the opportunity to join clubs and attend professional development workshops that take place on campus. These activities can significantly enrich your learning and development journey. Moreover, broadening your circle of friends to include those from other majors you find intriguing can open up new perspectives and opportunities.
Best of luck on your journey,
Sarah
Your question has sparked an engaging conversation with insightful responses. It's fantastic that you're still in college because this offers you a multitude of options. You have a valuable network right within your school.
I strongly recommend that you engage with your college counselor and professors. They are a full of knowledge and experience, ready to guide you.
Don't miss out on the opportunity to join clubs and attend professional development workshops that take place on campus. These activities can significantly enrich your learning and development journey. Moreover, broadening your circle of friends to include those from other majors you find intriguing can open up new perspectives and opportunities.
Best of luck on your journey,
Sarah
Will Eckert
Wealth Management Analyst
1
Answer
New York, New York
Updated
Will’s Answer
Hello - Great question!
Data analysis is a great career path to pursue as someone with interest and skills in applied mathematics!
To connect with others who share your interest, try joining a data science or data analysis club at your school. You would be surprised how many other students at your school share similar interests to you and would love to talk about data science. Additionally, you might find that an upperclassman at your school could serve as a great mentor. Often, these students will have been in the same position as you a few years earlier, and they would be able to share any regrets or advice they may have regarding their career path.
Another resource that could be helpful is meeting with your applied mathematics professors at your school. Many of these professors have professional contacts in the industry and would be happy to connect you with someone that works in the career field. Additionally, they may be working on a research project that they need a research assistant for, which could be an amazing opportunity to get hands on experience with data analysis.
You could also try to get a summer job/internship for a data analysis role. Internships can be a great way to connect with potential mentors and to feel out if a career field is a good fit for you. Furthermore, having real life experience through an internship can be instrumental in finding a job after college in that field.
Good luck on exploring this exciting field!
Data analysis is a great career path to pursue as someone with interest and skills in applied mathematics!
To connect with others who share your interest, try joining a data science or data analysis club at your school. You would be surprised how many other students at your school share similar interests to you and would love to talk about data science. Additionally, you might find that an upperclassman at your school could serve as a great mentor. Often, these students will have been in the same position as you a few years earlier, and they would be able to share any regrets or advice they may have regarding their career path.
Another resource that could be helpful is meeting with your applied mathematics professors at your school. Many of these professors have professional contacts in the industry and would be happy to connect you with someone that works in the career field. Additionally, they may be working on a research project that they need a research assistant for, which could be an amazing opportunity to get hands on experience with data analysis.
You could also try to get a summer job/internship for a data analysis role. Internships can be a great way to connect with potential mentors and to feel out if a career field is a good fit for you. Furthermore, having real life experience through an internship can be instrumental in finding a job after college in that field.
Good luck on exploring this exciting field!
Kim Arskii
Social Media Analyst
145
Answers
St. Augustine, Florida
Updated
Kim’s Answer
Finding a mentor and starting your journey in data analysis while studying applied mathematics is a great idea, and it's definitely possible to combine the two without it affecting your studies. First, look within your college for professors or faculty members who have expertise in data analysis. They can provide guidance and might even offer research opportunities. Attend related seminars, workshops, or guest lectures to meet professionals in the field. Networking with classmates who share your interests can also be beneficial.
Next, join relevant clubs or organizations, such as a data science or mathematics club, which often host events and provide resources to learn more about the field. Online platforms like LinkedIn can help you connect with professionals and mentors in data analysis. Don’t hesitate to reach out to them with specific questions or for advice; many are willing to help students.
To balance your interest in data analysis with your applied mathematics studies, try to integrate data analysis projects into your coursework whenever possible. For example, if you have a project or paper to write, choose a topic that allows you to apply data analysis techniques. Online courses and certifications can also be completed at your own pace, fitting around your academic schedule. By strategically combining your interests and leveraging available resources, you can effectively pursue both without compromising your studies.
Next, join relevant clubs or organizations, such as a data science or mathematics club, which often host events and provide resources to learn more about the field. Online platforms like LinkedIn can help you connect with professionals and mentors in data analysis. Don’t hesitate to reach out to them with specific questions or for advice; many are willing to help students.
To balance your interest in data analysis with your applied mathematics studies, try to integrate data analysis projects into your coursework whenever possible. For example, if you have a project or paper to write, choose a topic that allows you to apply data analysis techniques. Online courses and certifications can also be completed at your own pace, fitting around your academic schedule. By strategically combining your interests and leveraging available resources, you can effectively pursue both without compromising your studies.
Suleka Bhaskar,PMP®, CSM
Data Management Lead
5
Answers
Buffalo Grove, Illinois
Updated
Suleka’s Answer
It's great that you're seeking a mentor to guide you on the right path. You should definitely approach your college counselor or teachers for their valuable advice and recommendations. Don't hesitate or delay - become an active member of clubs that align with your interests. You can also expand your understanding of data analysis by enrolling in relevant courses.
anahu d
10
Answers
Phoenix, Arizona
Updated
anahu’s Answer
Combining your interest in data analysis with your studies in applied mathematics can be a great way to enhance your skill set and open up new career opportunities. Here are some steps to help you find a mentor and begin your journey in data analysis while balancing your academic commitments:
### Finding a Mentor
1. **Professors and Faculty:**
- **Talk to Professors:** Reach out to professors in your applied mathematics department who have expertise in data analysis. They can provide guidance, recommend resources, and might even have research opportunities.
- **Office Hours:** Utilize office hours to discuss your interests and seek advice on how to integrate data analysis into your studies.
2. **Academic Advisors:**
- **Consult Your Advisor:** Your academic advisor can help you plan your coursework to include relevant data analysis classes and recommend faculty members who can mentor you.
3. **Networking Events:**
- **Attend Workshops and Seminars:** Look for workshops, seminars, and guest lectures on data analysis or related fields. These events are great places to meet potential mentors.
- **Join Relevant Clubs:** Participate in student organizations or clubs focused on data science, statistics, or applied mathematics.
4. **Online Platforms:**
- **LinkedIn:** Use LinkedIn to connect with professionals in data analysis. Look for alumni from your college who are working in the field and reach out to them.
- **Professional Organizations:** Join organizations like the American Statistical Association (ASA) or the Institute for Operations Research and the Management Sciences (INFORMS). These organizations often have mentorship programs.
5. **Research Projects:**
- **Undergraduate Research:** Get involved in research projects that involve data analysis. This can provide practical experience and help you connect with mentors.
### Starting Your Journey in Data Analysis
1. **Coursework Integration:**
- **Select Relevant Electives:** Choose electives in statistics, computer science, or data science that complement your applied mathematics curriculum.
- **Interdisciplinary Projects:** Look for opportunities to apply data analysis techniques in your mathematics projects or coursework.
2. **Online Courses and Certifications:**
- **Online Learning Platforms:** Enroll in online courses on platforms like Coursera, edX, or Udacity. Courses in data analysis, machine learning, and data visualization can be particularly beneficial.
- **Certifications:** Consider pursuing certifications in data analysis tools and languages, such as Python, R, SQL, and Tableau.
3. **Practical Experience:**
- **Internships:** Apply for internships that focus on data analysis. Internships provide hands-on experience and can be a great way to apply your theoretical knowledge.
- **Projects:** Work on personal or group projects that involve data analysis. Platforms like Kaggle offer datasets and competitions that can help you practice and showcase your skills.
4. **Software and Tools:**
- **Learn Programming Languages:** Gain proficiency in programming languages commonly used in data analysis, such as Python and R.
- **Data Analysis Tools:** Familiarize yourself with data analysis tools and software like Excel, SQL, Tableau, and Power BI.
5. **Study Resources:**
- **Books and Journals:** Read books and academic journals on data analysis. "Introduction to Statistical Learning" and "Data Science for Business" are good starting points.
- **Online Communities:** Join online communities and forums like Stack Overflow, Reddit, and Data Science Central to learn from others and seek advice.
### Balancing with Your Studies
1. **Time Management:**
- **Create a Schedule:** Plan your time effectively to balance coursework, extracurricular activities, and self-study in data analysis.
- **Prioritize Tasks:** Focus on high-priority tasks and break down larger projects into manageable steps.
2. **Set Realistic Goals:**
- **Short-Term Goals:** Set achievable short-term goals for learning new skills or completing projects in data analysis.
- **Long-Term Goals:** Keep your long-term career goals in mind and align your activities accordingly.
3. **Leverage Academic Projects:**
- **Integrate Interests:** Whenever possible, incorporate data analysis into your applied mathematics assignments and projects.
- **Collaborate:** Work with classmates who share your interests to make the learning process more engaging and effective.
### Finding a Mentor
1. **Professors and Faculty:**
- **Talk to Professors:** Reach out to professors in your applied mathematics department who have expertise in data analysis. They can provide guidance, recommend resources, and might even have research opportunities.
- **Office Hours:** Utilize office hours to discuss your interests and seek advice on how to integrate data analysis into your studies.
2. **Academic Advisors:**
- **Consult Your Advisor:** Your academic advisor can help you plan your coursework to include relevant data analysis classes and recommend faculty members who can mentor you.
3. **Networking Events:**
- **Attend Workshops and Seminars:** Look for workshops, seminars, and guest lectures on data analysis or related fields. These events are great places to meet potential mentors.
- **Join Relevant Clubs:** Participate in student organizations or clubs focused on data science, statistics, or applied mathematics.
4. **Online Platforms:**
- **LinkedIn:** Use LinkedIn to connect with professionals in data analysis. Look for alumni from your college who are working in the field and reach out to them.
- **Professional Organizations:** Join organizations like the American Statistical Association (ASA) or the Institute for Operations Research and the Management Sciences (INFORMS). These organizations often have mentorship programs.
5. **Research Projects:**
- **Undergraduate Research:** Get involved in research projects that involve data analysis. This can provide practical experience and help you connect with mentors.
### Starting Your Journey in Data Analysis
1. **Coursework Integration:**
- **Select Relevant Electives:** Choose electives in statistics, computer science, or data science that complement your applied mathematics curriculum.
- **Interdisciplinary Projects:** Look for opportunities to apply data analysis techniques in your mathematics projects or coursework.
2. **Online Courses and Certifications:**
- **Online Learning Platforms:** Enroll in online courses on platforms like Coursera, edX, or Udacity. Courses in data analysis, machine learning, and data visualization can be particularly beneficial.
- **Certifications:** Consider pursuing certifications in data analysis tools and languages, such as Python, R, SQL, and Tableau.
3. **Practical Experience:**
- **Internships:** Apply for internships that focus on data analysis. Internships provide hands-on experience and can be a great way to apply your theoretical knowledge.
- **Projects:** Work on personal or group projects that involve data analysis. Platforms like Kaggle offer datasets and competitions that can help you practice and showcase your skills.
4. **Software and Tools:**
- **Learn Programming Languages:** Gain proficiency in programming languages commonly used in data analysis, such as Python and R.
- **Data Analysis Tools:** Familiarize yourself with data analysis tools and software like Excel, SQL, Tableau, and Power BI.
5. **Study Resources:**
- **Books and Journals:** Read books and academic journals on data analysis. "Introduction to Statistical Learning" and "Data Science for Business" are good starting points.
- **Online Communities:** Join online communities and forums like Stack Overflow, Reddit, and Data Science Central to learn from others and seek advice.
### Balancing with Your Studies
1. **Time Management:**
- **Create a Schedule:** Plan your time effectively to balance coursework, extracurricular activities, and self-study in data analysis.
- **Prioritize Tasks:** Focus on high-priority tasks and break down larger projects into manageable steps.
2. **Set Realistic Goals:**
- **Short-Term Goals:** Set achievable short-term goals for learning new skills or completing projects in data analysis.
- **Long-Term Goals:** Keep your long-term career goals in mind and align your activities accordingly.
3. **Leverage Academic Projects:**
- **Integrate Interests:** Whenever possible, incorporate data analysis into your applied mathematics assignments and projects.
- **Collaborate:** Work with classmates who share your interests to make the learning process more engaging and effective.
Nadra Khan
Chief of Staff
1
Answer
Jersey City, New Jersey
Updated
Nadra’s Answer
Hello Jane! You'll find that numerous businesses and corporations possess a department dedicated to operations or technology. Data is truly omnipresent! You'll be amazed at how many individuals you encounter are intricately connected to data. It's a fascinating world out there!
James Constantine Frangos
Consultant Dietitian & Software Developer since 1972 => Nutrition Education => Health & Longevity => Self-Actualization.
6175
Answers
Gold Coast, Queensland, Australia
Updated
James Constantine’s Answer
Hi Jane, it’s great that you’re interested in data analysis!
Combining your applied mathematics background with data analysis is a fantastic path to explore. Here’s a breakdown of how you can find a mentor and start your journey:
1. Identifying Your Goals and Interests:
What kind of data analysis excites you? Is it analyzing financial data, understanding customer behavior, predicting trends, or something else entirely?
What are your long-term career aspirations? Do you see yourself working in a specific industry, like finance or healthcare, or are you open to exploring different options?
2. Finding a Mentor:
Your College Network:
Professors: Reach out to professors in your mathematics department who specialize in statistics, data science, or related fields. They might be able to offer guidance, connect you with research opportunities, or even become your mentor.
Career Services: Your college’s career services office often has resources and programs to connect students with mentors in various fields.
Student Clubs: Look for data science, analytics, or coding clubs at your college. These clubs can be great places to meet like-minded individuals and potential mentors.
Online Communities:
LinkedIn: Connect with professionals in data analysis and related fields. You can send personalized messages expressing your interest in learning and seeking mentorship.
Data Science Forums: Websites like Stack Overflow, Kaggle, and Reddit have active communities where you can ask questions, learn from others, and potentially find mentors.
Meetup Groups: Search for data science or analytics meetups in your area. These events offer opportunities to network and connect with professionals.
Professional Organizations:
The American Statistical Association (ASA): The ASA has a mentorship program and other resources for students interested in statistics and data analysis.
The Institute of Mathematical Statistics (IMS): The IMS offers similar resources and opportunities for students interested in mathematical statistics.
3. Combining Data Analysis with Your Studies:
Electives: Take elective courses in statistics, data mining, machine learning, or programming languages like Python or R. These courses will provide you with the foundational skills needed for data analysis.
Research Projects: Look for research opportunities within your mathematics department or other departments that involve data analysis. This hands-on experience will be invaluable.
Personal Projects: Start working on personal data analysis projects. You can find datasets online and use them to practice your skills. This is a great way to build your portfolio and demonstrate your abilities.
Online Courses: Platforms like Coursera, edX, and Udacity offer a wide range of data analysis courses. These courses can supplement your formal education and help you develop specific skills.
4. Key Skills to Develop:
Programming: Learn a programming language like Python or R, which are widely used in data analysis.
Statistics: Develop a strong foundation in statistical concepts and methods.
Data Visualization: Learn how to create informative and visually appealing data visualizations.
Machine Learning: Explore basic machine learning algorithms and their applications.
Communication: Be able to effectively communicate your findings to both technical and non-technical audiences.
Remember:
Be proactive: Reach out to potential mentors, attend events, and actively seek opportunities to learn and grow.
Be patient: Finding a mentor and building your data analysis skills takes time and effort.
Be persistent: Don’t give up if you face challenges. Embrace the learning process and celebrate your progress.
By following these steps, you can successfully combine your applied mathematics background with data analysis and embark on a fulfilling career path. Good luck!
God Bless,
JC.
Combining your applied mathematics background with data analysis is a fantastic path to explore. Here’s a breakdown of how you can find a mentor and start your journey:
1. Identifying Your Goals and Interests:
What kind of data analysis excites you? Is it analyzing financial data, understanding customer behavior, predicting trends, or something else entirely?
What are your long-term career aspirations? Do you see yourself working in a specific industry, like finance or healthcare, or are you open to exploring different options?
2. Finding a Mentor:
Your College Network:
Professors: Reach out to professors in your mathematics department who specialize in statistics, data science, or related fields. They might be able to offer guidance, connect you with research opportunities, or even become your mentor.
Career Services: Your college’s career services office often has resources and programs to connect students with mentors in various fields.
Student Clubs: Look for data science, analytics, or coding clubs at your college. These clubs can be great places to meet like-minded individuals and potential mentors.
Online Communities:
LinkedIn: Connect with professionals in data analysis and related fields. You can send personalized messages expressing your interest in learning and seeking mentorship.
Data Science Forums: Websites like Stack Overflow, Kaggle, and Reddit have active communities where you can ask questions, learn from others, and potentially find mentors.
Meetup Groups: Search for data science or analytics meetups in your area. These events offer opportunities to network and connect with professionals.
Professional Organizations:
The American Statistical Association (ASA): The ASA has a mentorship program and other resources for students interested in statistics and data analysis.
The Institute of Mathematical Statistics (IMS): The IMS offers similar resources and opportunities for students interested in mathematical statistics.
3. Combining Data Analysis with Your Studies:
Electives: Take elective courses in statistics, data mining, machine learning, or programming languages like Python or R. These courses will provide you with the foundational skills needed for data analysis.
Research Projects: Look for research opportunities within your mathematics department or other departments that involve data analysis. This hands-on experience will be invaluable.
Personal Projects: Start working on personal data analysis projects. You can find datasets online and use them to practice your skills. This is a great way to build your portfolio and demonstrate your abilities.
Online Courses: Platforms like Coursera, edX, and Udacity offer a wide range of data analysis courses. These courses can supplement your formal education and help you develop specific skills.
4. Key Skills to Develop:
Programming: Learn a programming language like Python or R, which are widely used in data analysis.
Statistics: Develop a strong foundation in statistical concepts and methods.
Data Visualization: Learn how to create informative and visually appealing data visualizations.
Machine Learning: Explore basic machine learning algorithms and their applications.
Communication: Be able to effectively communicate your findings to both technical and non-technical audiences.
Remember:
Be proactive: Reach out to potential mentors, attend events, and actively seek opportunities to learn and grow.
Be patient: Finding a mentor and building your data analysis skills takes time and effort.
Be persistent: Don’t give up if you face challenges. Embrace the learning process and celebrate your progress.
By following these steps, you can successfully combine your applied mathematics background with data analysis and embark on a fulfilling career path. Good luck!
God Bless,
JC.
Emily Katz
Data Analyst
3
Answers
Portland, Oregon
Updated
Emily’s Answer
Hi Jane!
I think that your background in applied mathematics will be extremely useful for a career in data analysis! A big part of any data analysis job is problem-solving, which I imagine your degree is definitely teaching you. My best advice would be to find a fun data project to work on in your spare time, so you have something tangible you can show future employers once you graduate. You can use a variety of coding languages for data analysis, but I would recommend R or Python. If you use R, check out "TidyTuesday". Each week a random dataset is posted and anyone can attempt to make a data visualization based on the dataset. It can be a great way to practice your skills, as well as connect with others in this space and potentially find a mentor. You can find more info here: https://github.com/rfordatascience/tidytuesday. Another community to check out is called R-Ladies. Consider joining the slack community, and you might be able to find a data analysis mentor there! https://rladies.org/
Best of luck on your data analysis journey!
I think that your background in applied mathematics will be extremely useful for a career in data analysis! A big part of any data analysis job is problem-solving, which I imagine your degree is definitely teaching you. My best advice would be to find a fun data project to work on in your spare time, so you have something tangible you can show future employers once you graduate. You can use a variety of coding languages for data analysis, but I would recommend R or Python. If you use R, check out "TidyTuesday". Each week a random dataset is posted and anyone can attempt to make a data visualization based on the dataset. It can be a great way to practice your skills, as well as connect with others in this space and potentially find a mentor. You can find more info here: https://github.com/rfordatascience/tidytuesday. Another community to check out is called R-Ladies. Consider joining the slack community, and you might be able to find a data analysis mentor there! https://rladies.org/
Best of luck on your data analysis journey!
Himani Dittakavi
Technology
4
Answers
Cary, North Carolina
Updated
Himani’s Answer
Hi Jane,
To find a mentor, I would recommend asking your teacher or professor (if in college) and make connections based on who they recommend, or you can even ask them to mentor you. Definitely asking your favorite teacher or professor who you feel most impacted you would be ideal in finding the right mentor-mentee connection. You can really start anywhere with your interest in data analytics. There are LinkedIn learning courses, community college classes and you can even watch YouTube videos if you are a beginner!
Hope this helps!
To find a mentor, I would recommend asking your teacher or professor (if in college) and make connections based on who they recommend, or you can even ask them to mentor you. Definitely asking your favorite teacher or professor who you feel most impacted you would be ideal in finding the right mentor-mentee connection. You can really start anywhere with your interest in data analytics. There are LinkedIn learning courses, community college classes and you can even watch YouTube videos if you are a beginner!
Hope this helps!
Kate Michelini
College
2
Answers
New York, New York
Updated
Kate’s Answer
Hello!
LinkedIn is an excellent platform to discover a mentor. You can begin by searching for individuals who are currently engaged in the career you aspire to pursue. It's beneficial to identify people with whom you share commonalities, such as attending the same school or residing in the same locality. A Chrome extension like Apollo.io can be handy to obtain their email addresses.
Once you have their email, draft a concise message requesting a brief 15-minute conversation. In your message, suggest some possible dates and times for the call, but also express your flexibility. To capture their interest, include a reference to your shared connection in the subject line. If you don't receive a response within three days, don't hesitate to send a follow-up email. To increase the likelihood of securing a call, consider reaching out to multiple people.
Before the call, it's important to familiarize yourself with their LinkedIn profile and prepare a list of questions to ask. Begin the call with a brief one-minute introduction of yourself, then proceed to your questions. Be mindful of their time throughout the call.
After the call, send a thank you email detailing specific points of the conversation you found valuable. If the call went well, consider maintaining the connection. Reach out again in about a month, keeping them updated on your career progression and continue seeking their advice.
I trust you'll find this information beneficial!
LinkedIn is an excellent platform to discover a mentor. You can begin by searching for individuals who are currently engaged in the career you aspire to pursue. It's beneficial to identify people with whom you share commonalities, such as attending the same school or residing in the same locality. A Chrome extension like Apollo.io can be handy to obtain their email addresses.
Once you have their email, draft a concise message requesting a brief 15-minute conversation. In your message, suggest some possible dates and times for the call, but also express your flexibility. To capture their interest, include a reference to your shared connection in the subject line. If you don't receive a response within three days, don't hesitate to send a follow-up email. To increase the likelihood of securing a call, consider reaching out to multiple people.
Before the call, it's important to familiarize yourself with their LinkedIn profile and prepare a list of questions to ask. Begin the call with a brief one-minute introduction of yourself, then proceed to your questions. Be mindful of their time throughout the call.
After the call, send a thank you email detailing specific points of the conversation you found valuable. If the call went well, consider maintaining the connection. Reach out again in about a month, keeping them updated on your career progression and continue seeking their advice.
I trust you'll find this information beneficial!