Salary for Mid-level / Intermediate Data Analytics Manager during 2023

Salary details

The average mid-level / intermediate Data Analytics Manager salary lies between USD 116,200 and USD 155,000 globally. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Nov. 17, 2024

Salary trend

Top 20 Job Tags for Mid-level / Intermediate Data Analytics Manager roles

The three most common job tag items assiciated with mid-level / intermediate Data Analytics Manager job listings are Data Analytics, SQL and Engineering. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:

Data Analytics | 21 jobs SQL | 12 jobs Engineering | 10 jobs Statistics | 10 jobs Python | 9 jobs Tableau | 8 jobs Research | 8 jobs R | 7 jobs Agile | 7 jobs Consulting | 6 jobs CX | 6 jobs Data analysis | 6 jobs Machine Learning | 5 jobs Power BI | 5 jobs Architecture | 5 jobs Data visualization | 5 jobs E-commerce | 5 jobs ETL | 4 jobs AWS | 4 jobs Business Intelligence | 4 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Data Analytics Manager roles

The three most common job benefits and perks assiciated with mid-level / intermediate Data Analytics Manager job listings are Career development, Startup environment and Flex hours. Below you find a list of the 20 most occuring job perks or benefits in 2023 and the number of open jobs that where offering them during that period:

Career development | 15 jobs Startup environment | 12 jobs Flex hours | 10 jobs Flex vacation | 8 jobs Parental leave | 6 jobs Health care | 6 jobs Competitive pay | 4 jobs Equity / stock options | 3 jobs Team events | 3 jobs Insurance | 2 jobs Salary bonus | 2 jobs 401(k) matching | 1 jobs Lunch / meals | 1 jobs Fitness / gym | 1 jobs Transparency | 1 jobs Conferences | 1 jobs Pet friendly | 1 jobs

Salary Composition

The salary for a Mid-level/Intermediate Data Analytics Manager typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or benefits. The composition can vary significantly based on region, industry, and company size. In tech hubs like Silicon Valley, the base salary might be higher, but bonuses and stock options can also form a substantial part of the total compensation package. In contrast, companies in regions with a lower cost of living might offer a smaller base salary but compensate with other benefits. Industries such as finance or healthcare may offer higher bonuses compared to non-profit sectors. Larger companies often provide more comprehensive benefits packages, including health insurance, retirement plans, and professional development opportunities.

Steps to Increase Salary

To increase your salary from this position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging technologies and tools in AI/ML and data science. Specializing in niche areas can make you more valuable.
• Advanced Education: Pursuing further education, such as a master's degree or an MBA, can open up higher-paying opportunities.
• Leadership Roles: Aim for roles with more responsibility, such as leading larger teams or managing cross-functional projects.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Performance Excellence: Consistently exceed performance expectations to position yourself for promotions and salary increases.

Educational Requirements

Most Mid-level/Intermediate Data Analytics Manager positions require at least a bachelor's degree in a relevant field such as computer science, statistics, mathematics, or engineering. However, many employers prefer candidates with a master's degree in data science, business analytics, or a related discipline. A strong educational background provides a solid foundation in analytical techniques and business acumen, which are crucial for this role.

Helpful Certifications

Certifications can enhance your credentials and demonstrate your expertise. Some valuable certifications include:

• Certified Analytics Professional (CAP)
• Google Data Analytics Professional Certificate
• Microsoft Certified: Azure Data Scientist Associate
• AWS Certified Machine Learning – Specialty
• SAS Certified Data Scientist

These certifications can validate your skills and knowledge, making you a more competitive candidate.

Required Experience

Typically, this role requires 5-7 years of experience in data analytics or a related field. Experience should include hands-on work with data analysis, statistical modeling, and machine learning. Additionally, experience in managing teams and projects is crucial, as this role often involves leading a team of data analysts and collaborating with other departments.

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