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Job outlook for senior data scientists in the United States
Are senior data scientist jobs in demand?
Senior data scientist job and salary trends over time
Senior data scientist jobs over time
Senior data scientist job growth rate over time
| Year | # of jobs | % of population |
|---|---|---|
| 2021 | 3,109 | 0.00% |
| 2020 | 2,969 | 0.00% |
| 2019 | 2,871 | 0.00% |
| 2018 | 2,631 | 0.00% |
| 2017 | 2,443 | 0.00% |
Average senior data scientist salary over time
Senior data scientist salary by year
| Year | Avg. salary | Hourly rate | % Change |
|---|---|---|---|
| 2025 | $124,093 | $59.66 | +3.4% |
| 2024 | $120,004 | $57.69 | +2.3% |
| 2023 | $117,287 | $56.39 | +3.4% |
| 2022 | $113,473 | $54.55 | +2.4% |
| 2021 | $110,817 | $53.28 | +1.1% |
Senior data scientist jobs by state
Most common states for senior data scientists
| Rank | State | Population | # of jobs | Employment/ 1000ppl |
|---|---|---|---|---|
| 1 | District of Columbia | 693,972 | 367 | 53% |
| 2 | Massachusetts | 6,859,819 | 1,576 | 23% |
| 3 | Maryland | 6,052,177 | 1,416 | 23% |
| 4 | New Hampshire | 1,342,795 | 292 | 22% |
| 5 | South Dakota | 869,666 | 185 | 21% |
| 6 | New Jersey | 9,005,644 | 1,784 | 20% |
| 7 | Alaska | 739,795 | 145 | 20% |
| 8 | Virginia | 8,470,020 | 1,614 | 19% |
| 9 | Oregon | 4,142,776 | 789 | 19% |
| 10 | Montana | 1,050,493 | 195 | 19% |
| 11 | Delaware | 961,939 | 187 | 19% |
| 12 | North Dakota | 755,393 | 146 | 19% |
| 13 | Connecticut | 3,588,184 | 639 | 18% |
| 14 | North Carolina | 10,273,419 | 1,705 | 17% |
| 15 | Minnesota | 5,576,606 | 892 | 16% |
| 16 | Utah | 3,101,833 | 509 | 16% |
| 17 | Illinois | 12,802,023 | 1,935 | 15% |
| 18 | Pennsylvania | 12,805,537 | 1,887 | 15% |
| 19 | Washington | 7,405,743 | 1,100 | 15% |
| 20 | Vermont | 623,657 | 93 | 15% |
Most common cities for senior data scientists
| Rank | City | # of jobs | Employment/ 1000ppl | Avg. salary |
|---|---|---|---|---|
| 1 | Annapolis | 17 | 43% | $99,258 |
| 2 | Hartford | 13 | 11% | $105,462 |
| 3 | Lansing | 12 | 10% | $92,992 |
| 4 | Atlanta | 33 | 7% | $88,193 |
| 5 | Des Moines | 12 | 6% | $92,033 |
| 6 | Tallahassee | 11 | 6% | $86,333 |
| 7 | Boston | 37 | 5% | $109,668 |
| 8 | Washington | 31 | 5% | $101,253 |
| 9 | Baton Rouge | 11 | 5% | $90,897 |
| 10 | San Francisco | 32 | 4% | $146,598 |
| 11 | Minneapolis | 18 | 4% | $88,665 |
| 12 | Sacramento | 14 | 3% | $146,291 |
| 13 | Chicago | 27 | 1% | $91,446 |
| 14 | Phoenix | 18 | 1% | $103,322 |
| 15 | Indianapolis | 12 | 1% | $83,303 |
| 16 | San Diego | 12 | 1% | $127,113 |
| 17 | San Jose | 11 | 1% | $145,548 |
| 18 | New York | 24 | 0% | $111,586 |
| 19 | Los Angeles | 13 | 0% | $134,309 |
Senior Data Scientist job outlook: Expert opinions
Our panel of senior data scientist experts
Kennesaw State University
University of California - Davis
Ohio State University
Adelphi University
San Francisco State University
Kennesaw State University
Utah State University
Cumberland University
Texas A&M University
Pennsylvania State University
Robert Morris University
Medical College of Wisconsin
Louisiana State University and A&M College
Pacific University
What general advice would you give to a Senior Data Scientist?
Dr. Partha Sengupta: Data processing and data science have a rapid growth in job market about 35% which is faster in growth than any other streams of Computer Science. Data is the new petroleum of the modern age. Data storage and management in cloud-based infrastructure, understanding data storage in relational and non-relational databases and secure catching configuration, global accessibility and collaboration of data, data privacy and security, preprocessing and using advanced algorithms to analyze data is the current and future requirement. You are going to take center stage in all other end software applications which will need a robust and secure data workflow for successful implementation of the process.
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
Dr. Partha Sengupta: Skills of data privacy like anonymization, aggregation, user-centric privacy control, homomorphic encryption, and federated learning algorithms. Database security that protects the confidentiality, integrity, and availability of an organization. Using adaptive security systems in this field is very important for automation of data storage and accessibility. Understanding data privacy laws like General Data Protection Regulation (GDPR) used in Europe, USA laws like California Consumer Privacy Act (CCPA) etc. and more cybersecurity laws and ethics to evolve in the future for dynamic nature of data workflow, such that the students understand compliance with myriads of data protection regulations as per individual country, continents, and global data protection and privacy laws. Students should also be aware of quantum computing mechanisms and post-quantum encryption process. Another important aspect is edge computing which involves data processing at the edge, real-time decision-making, optimized data transmission, distributed architecture, and scalability and flexibility. Understanding A.I. models used in multimodal learning process like audio, video, images, 3D maps, natural language processing (NLP) and deep learning algorithms, generative transformer models which correlated relation between words in a sentence using a technique called self-attention, local training of data using A.I models in a distributive network called Federated learning.
What will help Senior Data Scientists increase their earning potential?
Dr. Partha Sengupta: Fit to jobs like Data Controllers and Data Processors understanding both USA and International data privacy and protection laws, implementing data protection into system and processes, auditing, authentication, and access control. Creators of robust and secured databases and recommender systems using collaborative, content, hybrid and contextual filtering. One such example is Deep Learning Recommendation Learning (DLRM). Data storage, processability and usage in edge computing in IoT devices including personalized chatbots. Running A.I. (AIoT), analytics, and other business capabilities on IoT devices, consolidate edge data at scale and eliminate data silos, deploy manage and help secure edge workloads remotely, optimize the costs of running edge solutions, and enable devices to react faster to local changes. Handling data related to medical instruments, medical chatbots, and usage of A.I for data analytics in application of telemedicine, diagnosis accuracy, and medical laboratories. Medical data analytics of A.I application in mental health disorders (MHD) and medical image classification. Another important aspect of genetic data and the application of A.I on it. Language Model architectures using human language data, deep learning algorithms, and application of generative transformers
What general advice would you give to a Senior Data Scientist?
Dr. Devin Rafferty PhD: In three to five years most of the data scientists will have programmed themselves out of employment, which we're really already starting to see the acceleration of. However, there is one skill that is essentially timeless and will remain so, which is the ability to coherently integrate multiple aspects of interdisciplinary information in an uncertain environment to form a hypothesis about the future and then assign a level of confidence to that statement.
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
Dr. Devin Rafferty PhD: By far, the biggest thing that I would emphasize to recent graduates is to *never* underestimate the value of showing up early, being prepared to work (which means having read, analyzed, and synthesized all of the required documents), and having a smile on their face. If you can do that consistently, you'll always be way ahead of the curve.
What will help Senior Data Scientists increase their earning potential?
Dr. Devin Rafferty PhD: Read anything and everything, especially history. There is an enormous value that someone can gain simply from understanding how different disciplines fit together, because the real-world is not segmented into sociology, politics, economics, etc.; rather it is all one dynamic system. For example, when students ask me what they should really focus on reading to prepare for their careers, I usually respond by asking what *exactly* will be their careers in fifteen years--which is frequently met with indecision. The point is that one should not tailor their knowledge and skill sets to an expected career; rather, just the opposite, one should learn *everything* that the brain can absorb and then the skill sets needed for the career will already be there--and obtaining promotions will be fairly straightforward.
Cornelius Nelan Prof.
Professor of MathematicsWhat general advice would you give to a Senior Data Scientist?
Cornelius Nelan Prof.: I would say that it is a good idea to visit the career placement center in your school to get help writing a resume. When you apply, write a cover letter that is specifically tailored to the job description and explain how you would uniquely be qualified for the position. Do some research into the company and explain why you are interested in the job.
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
Cornelius Nelan Prof.: Advanced topics are gravy, you should be grounded in the basics: Precalculus skills (especially trigonometry and algebra), Calculus, and Linear Algebra. It is also good to have a background in statistics, and computer science (Learn a computer language, such as Java.) Given the job market today, you should be somewhat familiar with Data Science and AI. If you have time take some business (especially Finance) classes. It is also important to be able to work in group settings. An important skill is your ability to communicate (orally and in writing) to mathematicians but also to non-mathematicians. If you can find a professor who is willing to supervise (and give credit for) some independent research project, do so. It is important to demonstrate that you can work independently (do literature searches, work problems out for yourself). Include this in your resume. It would also be good to get some experience tutoring mathematics (to non-majors or majors). Again, this demonstrates your ability to communicate.
What will help Senior Data Scientists increase their earning potential?
Cornelius Nelan Prof.: Emphasize your ability to learn mathematics independently, and work with groups. In your cover letter emphasize your ability to grow and adapt to the job you are applying for. Even after you find a job, keep looking; something better may come up.
What general advice would you give to a Senior Data Scientist?
Dr. Ali Fridley Ph.D.: Networking skills and the ability to build relationships are paramount. Be a lifelong student. Learn from those around you, especially those you admire. Know your strengths and use them. On the other hand, understand your weaknesses and surround yourself with people who are skilled in those areas.
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
Dr. Ali Fridley Ph.D.: I believe there is a growing need for employees skilled in analytics and artificial intelligence. Understanding not only how, but also when it is appropriate to use it will be extremely important.
What will help Senior Data Scientists increase their earning potential?
Dr. Ali Fridley Ph.D.: To be honest, when starting out in an entry-level position, there is not a lot of room for salary negotiation.
What general advice would you give to a Senior Data Scientist?
Dr. Yeol Huh: Avoid falling for the myth of adopting technology just for its own sake. Although it's tempting to experiment with the latest innovations, your approach should be grounded in fundamentals. Begin by defining the goals or outcomes you wish to achieve, and consider relevant theories that guide your approach.
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
Dr. Yeol Huh: Pursuing certification programs in data analytics and AI fundamentals, offered by organizations like Google or Microsoft, can be beneficial before starting your career. Additionally, securing an internship to gain firsthand experience in the field can significantly enhance your salary potential. Lastly, developing an electronic portfolio where you can compile the works you have done and showcase your skills and knowledge can be an extra help.
What will help Senior Data Scientists increase their earning potential?
Dr. Yeol Huh: Data literacy is undoubtedly one of the most crucial skills in the field today. Understanding how to identify, collect, analyze data, and make data-driven decisions will be key competencies in the next 3-5 years. This will increasingly include AI literacy, enabling you to identify and apply appropriate AI technologies to your specific contexts.
What general advice would you give to a Senior Data Scientist?
Yubei Chen: In addition to the emerging AI tools, I feel data skill is also going to be important. AI models are trained on massive data. How to prepare, curate large-scale high-quality data will become an important trade.
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
Yubei Chen: When there is a new technology, there is usually a shift in job opportunities. I think it is increasingly more important for the young generations to learn how to use the emerging AI tools to efficiently accomplish their jobs, for example coding copilot, chatGPT, generative models, etc.
What will help Senior Data Scientists increase their earning potential?
Yubei Chen: Try to play with AI tools. AI as a generic technology is moving very fast. This is a unique opportunity for the young generation. In addition to the problem-solving ability, please also improve your information curation skills.
Professor Todd Thompson
Astronomy Chair (potentially)Ohio State University
Astronomy And Astrophysics
What general advice would you give to a Senior Data Scientist?
Professor Todd Thompson: Depending on the positions applied for, it is beneficial to do lots of “coding interview practice” and general interview practice. There are resources for learning algorithms and the types of questions asked in the technical parts of interviews. Separate from that, one should have a webpage (e.g., github) potentially with active coding projects. Separate from that, one should have a linkedin page and work to develop contacts at various companies. Contacts can help you get past the initial triage phase for a job and to the interview stage. Networking.
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
Professor Todd Thompson: There is a big obvious shift towards AI/ML-enabled data discovery. Regardless of sub-field, students should develop proficiency with general data science tools and they should keep up on new developments in AI/ML (e.g., Pytorch).
What will help Senior Data Scientists increase their earning potential?
Professor Todd Thompson: Work hard. Be curious. Develop microskills associated with your science projects, but also the macroskills needed to develop and lead projects: question-asking, conceptualization, data interrogation, reading and writing.
What general advice would you give to a Senior Data Scientist?
Dr. Shana Caro: Graduates can maximize their salary potential by finding jobs that suit their own strengths, and writing a convincing cover letter that tells hiring managers just how much value they can add to the company. They can also research starting salaries in their chosen career, and negotiate their salaries based on that evidence. Graduates can also consider moving to areas with higher paying jobs. Finally, graduates should consider and ask what criteria their bosses will use when evaluating their work output; essentially, they should find out what matters most to the company or boss, and work hardest on those metrics. There has also been a tension between the graduates' desire for remote work and companies' preference for in-person work. Graduates should consider flexibility in their working arrangements, since how happy your supervisors are with you may determine whether you get raises and promotions. Putting in face time can help you stand out in an increasingly remote world.
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
Dr. Shana Caro: Graduates beginning their careers should always think about their personal growth and strengths. When picking a career, consider what your strengths are. If you are good at computer programming, pick a career like software design. If you are good at translating complex scientific results into clear English, pick a career like data sciences, sales for a biotech company, or medical writing. In every job, have goals for the skills you want to develop and work on those. Find a mentor in your work who can help you accomplish those.
What will help Senior Data Scientists increase their earning potential?
Dr. Shana Caro: In the next 3-5 years, graduates will want to have a mix of hard and soft skills. As AI and LLMs become more powerful and prevalent, being able to use these new tools effectively will be incredibly helpful in a variety of industries. Coming up with the right prompts to direct these models is a high-level skill that takes practice. In data science jobs, which Biological and Physical Science majors would excel at, basic computer programming in any language, data visualization, and understanding A-B testing will be important. The value-add of graduates in these majors is frequently that they can translate mathematical results into business insights in plain English and clear data visualizations. Additionally, graduates will also have to focus on their soft skills -- especially communicating with their managers and teammates in a professional and effective manner. Finally, flexibility is a key soft skill in any field. Graduates should be able to take criticism and improve their work, and be excited to learn new technical skills.
Dr. Bob Patterson DNP, MSN, RN
ProfessorSan Francisco State University
Registered Nursing, Nursing Administration, Nursing Research And Clinical Nursing
What general advice would you give to a Senior Data Scientist?
Dr. Bob Patterson DNP, MSN, RN: I would advise graduates starting their career in the field to focus on continuous learning, networking, and gaining practical experience. It's essential to stay updated with the latest trends and technologies in the field to remain competitive.
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
Dr. Bob Patterson DNP, MSN, RN: In the next 3-5 years, skills such as data analysis, digital literacy, and intercultural communication will become increasingly important in the field. Employers are looking for candidates who can adapt to rapidly changing environments and work effectively with diverse teams.
What will help Senior Data Scientists increase their earning potential?
Dr. Bob Patterson DNP, MSN, RN: To maximize your salary potential when starting your career in the field, it's crucial to negotiate your starting salary based on your qualifications, experience, and the market demand for your skills. Additionally, pursuing advanced certifications and specializations can increase your earning potential in the long run.
What general advice would you give to a Senior Data Scientist?
Dr. Pengcheng Xiao: For recent graduates entering the field of mathematics, my advice is to build a strong foundation in fundamental concepts, hone problem-solving skills through practice, embrace collaboration with peers and professionals, stay curious about new developments, and communicate effectively to convey ideas and findings.
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
Dr. Pengcheng Xiao: Over the next 3-5 years, skills such as data science and machine learning, computational mathematics, interdisciplinary collaboration, cybersecurity and cryptography, and ethical reasoning will become increasingly important in the field of mathematics, reflecting the growing demand for expertise in data analysis, algorithm development, interdisciplinary problem-solving, cybersecurity, and ethical considerations in mathematical applications.
What will help Senior Data Scientists increase their earning potential?
Dr. Pengcheng Xiao: Maximizing salary potential when starting a career in mathematics involves pursuing advanced degrees or certifications, gaining practical experience through internships and research opportunities, acquiring in-demand skills such as programming and data analysis, negotiating effectively for competitive compensation packages, and staying updated with market trends to identify opportunities for career advancement and higher salaries.
What general advice would you give to a Senior Data Scientist?
Polly Conrad: To maximize your salary potential when starting your career, consider the following strategies:
1. Specialize in High-Demand Areas: Focus on acquiring skills in high-demand areas such as AI, cybersecurity, and cloud computing. Specialized skills often command higher salaries. 2. Certifications and Advanced Degrees: Earning certifications in relevant technologies and methodologies can enhance your qualifications and make you more competitive. Consider pursuing advanced degrees if they align with your career goals (Utah State University Graduate Certificates). 3. Negotiate Effectively: Don’t hesitate to negotiate your salary and benefits when you receive a job offer. Research industry salary standards and be prepared to articulate your value to potential employers. 4. Gain Diverse Experience: Seek roles that offer diverse experiences and opportunities for growth. Working in various industries and on different types of projects can broaden your skill set and increase your marketability. 5. Stay Informed: Keep abreast of industry trends and salary benchmarks. Understanding the market dynamics can help you make informed decisions about job opportunities and career moves.
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
Polly Conrad: Entering the job market with a degree in Information Systems or Data Analytics can be both exciting and daunting. The landscape of these fields is dynamic, with continuous advancements in technology and methodologies. Here are some key pieces of advice for new graduates:
1. Embrace Lifelong Learning: The tech industry evolves rapidly, and staying relevant requires continuous learning. Engage in professional development opportunities, attend workshops, and earn certifications in emerging technologies and methodologies (Utah State University Graduate Certificates). 2. Network Actively: Building a strong professional network can open doors to job opportunities and career advancements. Attend industry conferences, join professional associations, and leverage platforms like LinkedIn to connect with industry professionals. 3. Seek Mentorship: Finding a mentor can provide invaluable guidance and insights. Mentors can help you navigate your career path, offer advice on skill development, and provide support during challenging times. 4. Gain Practical Experience: Internships, co-op programs, and project-based work can provide hands-on experience that is highly valued by employers (Utah State University Analytics Solutions Center). Practical experience helps you apply theoretical knowledge to real-world problems and enhances your resume.
What will help Senior Data Scientists increase their earning potential?
Polly Conrad: The fields of Information Systems and Data Analytics are continuously evolving, and several skills are expected to become increasingly important over the next 3-5 years:
1. Data Literacy: As data becomes more integral to decision-making, the ability to understand, interpret, and communicate data insights will be crucial. 2. Artificial Intelligence and Machine Learning: Proficiency in AI and ML will be highly sought after, as these technologies drive innovation across various industries. 3. Cybersecurity: With the growing number of cyber threats, skills in cybersecurity will be essential to protect data and ensure the integrity of information systems. 4. Cloud Computing: Expertise in cloud platforms and services will be critical as organizations continue to migrate their operations to the cloud. 5. Soft Skills: Communication, teamwork, and problem-solving skills are always in demand. The ability to work effectively in diverse teams and communicate technical concepts to non-technical stakeholders will set you apart.
What general advice would you give to a Senior Data Scientist?
John Phillips: Gain experience through undergraduate research and seek opportunities that capitalize on the unique skills acquired during laboratory work. Employers highly value new graduates who are already proficient with the instruments and software relevant to their field. Additionally, having experience in a topic aligned with a company's current projects can provide an extra advantage.
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
John Phillips: With the continuous advancement of computational processing power, having a strong grasp of software programming and data analysis becomes progressively more advantageous. The widespread adoption of Machine Learning techniques in various industries has empowered many new companies to tackle chemical problems that were previously deemed too complex.
What will help Senior Data Scientists increase their earning potential?
John Phillips: Cultivate curiosity, dedication, and a strong network. While curiosity and hard work may come naturally, networking can be challenging. However, it's a vital skill that can open doors and create opportunities. Start by connecting with speakers who visit your department and engaging with fellow students at conferences.
What general advice would you give to a Senior Data Scientist?
Dr. Noa Stroop: 2. AI, machine learning, automation, cloud services, data management, lidar and radar
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
Dr. Noa Stroop: 3. First, the right mentality. Always look at situations positively, seek first to help others, be curious about your peers, and constantly look for opportunities to improve self. This creates rapport, which can be used to ask for more responsibilities, which can be leveraged for higher pay or promotion. Second, don't approach the job market with desperation. Too often, we don't have an income source, so we have to take the first offer that comes. 'The best time to look for a job is when you already have one', for it relieves desperation, gives you the power of choice. Finally, know your worth by doing research. But don't think that a degree replaces experience; it enhances it.
What will help Senior Data Scientists increase their earning potential?
Dr. Noa Stroop: 1. Always look to upskill. Technology changes so rapidly (Moore's Law) that one's expertise can become outdated in a remarkably short amount of time. Stay current on emerging technologies and seek out certifications to prove your adaptability and aptitude.
What general advice would you give to a Senior Data Scientist?
Nitesh Saxena: In the near-term, AI and ML are going to very important and highly sought-after skills. To pad along with that, cybersecurity is an essential area to make sure the AI models work the way they should even under the influence of an adversary. Privacy and ethics are not be ignored either as real-world AI must respect people’s privacy and societal boundaries.
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
Nitesh Saxena: The key would be to focus on continuous experiential learning and dynamically adjusting to the changing landscape of this beautiful field.
What will help Senior Data Scientists increase their earning potential?
Nitesh Saxena: What you learned in your degree program at a University is very foundational. It provides you the sufficient baseline to build on. To be successful in one’s career, one would need to focus on continuous learning starting from this base, and adapt and expand one’s skillsets according to the changing advancements in the field, and be a life-long learner.
Dr Paul Milewski
Head, Department of MathematicsPennsylvania State University
Applied Mathematics
What general advice would you give to a Senior Data Scientist?
Dr Paul Milewski: Because mathematics is a universal language of science, engineering, finance and data, Mathematicians can have many jobs. For example, mathematicians working as data scientists produce mathematical models and simulate them on computers in order to explain patterns in data. Mathematicians working in cryptography work in improving digital security by creating and breaking encryptions.
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
Dr Paul Milewski: We live in an age of mathematics: everything around you runs on math. Cell phones, AI and chat GPT, weather prediction, supply chains, drug development and modern medicine, etc… A math major or a minor is a springboard to many different areas for work and further study.
What will help Senior Data Scientists increase their earning potential?
Dr Paul Milewski: Mathematicians end up in such diverse jobs that its hard to generalize. We love the beauty and power of mathematics; we don’t particularly like everyone telling us they hate math!
What general advice would you give to a Senior Data Scientist?
Steve Mancini D.B.A.: Depending on your career field, because you are just starting out and thus do not have experience, to improve your worth, consider completing different certifications in whatever career field you are in. Not all certifications require experience so focus on any certification that can be achieved through study/testing/some hands-on work. This will likely set you apart from other candidates who may have a degree like you but also like you, have no experience. You can never downplay the importance of education, and the more you have, the more value you have right out of the gate. Also, consider joining professional organizations. Again, this shows a willingness to expand your knowledge, and it also allows you to meet individuals you may otherwise not be able to meet.
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
Steve Mancini D.B.A.: While we all understand the importance of technology, concepts that were mere theory or in their infancy just a few decades ago, such as Artificial Intelligence, have become mainstays in our daily lives. As such, being aware of new technology and being on the front edge of what was once theoretical is always a good skill to have. In this case, fields like AI, machine learning, data analytics, data analysis. etc. can now be expanded into every aspect of our lives thus resulting in even greater advances in the future. So, stay engaged in the learning process, don't get stale, things are always changing!
What will help Senior Data Scientists increase their earning potential?
Steve Mancini D.B.A.: First, I would seek the wisdom of those who are currently working in the field. That experience is important because it helps one determine which path may be best suited for them without having to repeat mistakes. Second, don't expect to know the exact job you will likely end up performing. Be flexible. Every opportunity to work gives you new experience and a new perspective so take advantage of whatever you are offered if it is even close to what you are interested in doing.
Prof. Kirsten Beyer
Director of PhD Program in Public and Community HealthMedical College of Wisconsin
Public Health
What general advice would you give to a Senior Data Scientist?
Prof. Kirsten Beyer: Be open to many possibilities and don’t get locked in to a linear path. Sometimes things will open up in unexpected ways.
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
Prof. Kirsten Beyer: Data science, community engagement
What will help Senior Data Scientists increase their earning potential?
Prof. Kirsten Beyer: Gaining experience and publishing; pursuing multiple positions to give you leverage; being confident and recognizing your own worth.
Jill Trepanier
Associate ProfessorLouisiana State University and A&M College
Atmospheric Sciences And Meteorology
What general advice would you give to a Senior Data Scientist?
Jill Trepanier: The more software and scripting languages that you learn, the better off you will be.
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
Jill Trepanier: Learn how to find, download, analyze, and understand big data related to the climate and atmosphere. And Geographic information systems.
What will help Senior Data Scientists increase their earning potential?
Jill Trepanier: Learn communication skills - including writing, speaking, and ways to create and communicate visualizations.
What general advice would you give to a Senior Data Scientist?
Dr. John Wilson PhD, MBA: AI-based tools, immersive technologies, and no code development tools (just to name a few), are in their infancy, but for the first time are accessible to all kinds of users, not just those who have deep technical knowledge. Those who learn to apply technologies like these in novel ways to develop innovative solutions addressing complex logistical, economic, geopolitical, and social problems, will be in high demand.
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
Dr. John Wilson PhD, MBA: Be intentional about gaining experience in more than one aspect of your field, or in multiple fields. This can mean taking on roles that aren’t as lucrative in the short term but provide you with a better understanding of how complex systems interact and how they are advancing with the infusion of technical complexity. These combinations of experiences and learning opportunities will help you to be more adaptable, hence more valuable than those who remain in safer, more static job roles that don’t provide exposure to the now ubiquitous dancing landscape of volatility and change.
What will help Senior Data Scientists increase their earning potential?
Dr. John Wilson PhD, MBA: Many of the jobs that will be in demand in the next few years don’t even exist yet, so be prepared for rapid changes in the way work gets done. This means that the ability to be flexible and adaptable is as important, or more so, than your field of study. Look for people who are experts in their field yet are challenging assumptions and pressing the frontier in terms of technology and innovation – learn from them, ask questions, volunteer to get involved rather than sitting on the sidelines waiting to see what happens.
What general advice would you give to a Senior Data Scientist?
John Mayberry PhD: For students who want to directly use their math skills without graduate work, actuarial science can be a profitable career as it typically only requires an undergraduate degree to get started. In this case, it is recommended that students do an internship while completing their degree and pass one or two of the actuarial exams before graduating. Data science is another profitable area, but students who wish to earn top salaries in this field should look into biostatistics or machine learning applications and consider pursuing a masters’ degree in biostatistics, data science, business analytics, or a related area. Finance is a third option which often requires a secondary major or minor in business.
What Senior Data Scientist skills would you recommend for someone trying to advance their career?
John Mayberry PhD: Combining your mathematical knowledge with computing skills is critical in today’s landscape. Learning to code in Python, R, Matlab, or C++ will strengthen your toolkit for tackling complex problems and increase your marketability in the field. In addition, the ability to analyze data using rigorous statistical methods and data visualization techniques will continue to be important in coming years. Storytelling, whether through words or visualizations, is often overlooked as an important skill, but mathematicians learn a great deal about putting together stories out of numbers and that is a highly competitive skill.
What will help Senior Data Scientists increase their earning potential?
John Mayberry PhD: A degree in mathematics will always pay off. Students of the subject have the adaptability to work in a large number of fields including finance, economics, engineering, biostatistics, data science, actuarial science, education, machine learning, and software development. The problem-solving and critical thinking skills that math majors learn are heavily sought after by employers. For students who want to teach, there are numerous opportunities at the secondary level and math teachers are some of the most sought after in the current market. For students who want to work in government/industry, it is often advisable to combine your math degree with a secondary major or minor such as economics, computer science, public policy, business, or engineering. Unexpected combinations with fields such as graphic design, literature, or communication can also open up opportunities in data visualization and storytelling.