Data Strategy Lead Salary in United States during 2024
💰 The median Data Strategy Lead Salary in United States during 2024 is USD 136,500
✏️ This salary info is based on 12 individual salaries reported during 2024
Salary details
The average Data Strategy Lead salary lies between USD 110,000 and USD 185,000 in the United States. 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.
- Job title
- Data Strategy Lead
- Experience
- all levels
- Region
- United States
- Salary year
- 2024
- Sample size
- 12
- Top 10%
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- Top 25%
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- Median
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- Bottom 25%
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- Bottom 10%
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Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.
Last updated:Top 20 Job Tags for Data Strategy Lead roles
The three most common job tag items assiciated with Data Strategy Lead job listings are Data strategy, Architecture and Consulting. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:
Data strategy | 37 jobs Architecture | 16 jobs Consulting | 15 jobs Data management | 13 jobs Engineering | 10 jobs Data Analytics | 9 jobs Security | 8 jobs Agile | 8 jobs Data governance | 8 jobs SQL | 7 jobs Research | 7 jobs Data quality | 7 jobs Tableau | 6 jobs Excel | 6 jobs KPIs | 6 jobs Data visualization | 6 jobs Data analysis | 6 jobs Privacy | 6 jobs Big Data | 5 jobs Banking | 5 jobsTop 20 Job Perks/Benefits for Data Strategy Lead roles
The three most common job benefits and perks assiciated with Data Strategy Lead job listings are Career development, Startup environment and Health care. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:
Career development | 23 jobs Startup environment | 15 jobs Health care | 9 jobs Competitive pay | 8 jobs Wellness | 5 jobs Medical leave | 5 jobs Flex hours | 3 jobs Team events | 3 jobs Insurance | 3 jobs 401(k) matching | 2 jobs Equity / stock options | 2 jobs Relocation support | 2 jobs Salary bonus | 2 jobs Parental leave | 1 jobs Flex vacation | 1 jobs Gear | 1 jobs Fitness / gym | 1 jobs Signing bonus | 1 jobsSalary Composition for a Data Strategy Lead
The salary for a Data Strategy Lead in the United States typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or benefits. The base salary often constitutes the majority of the total compensation package, usually ranging from 70% to 85%. Performance bonuses can vary significantly depending on the company and industry, often ranging from 10% to 20% of the total compensation. Additional remuneration, such as stock options, profit-sharing, or other benefits, can make up the remaining 5% to 10%.
Regional differences can also impact salary composition. For instance, tech hubs like San Francisco or New York may offer higher base salaries and stock options due to the competitive market. In contrast, companies in smaller cities might offer a higher percentage of bonuses to attract talent. Industry and company size also play a role; larger tech companies or financial institutions might offer more comprehensive stock options, while smaller startups might focus on bonuses and flexible work arrangements.
Steps to Increase Salary from a Data Strategy Lead Position
To increase your salary from a Data Strategy Lead position, consider the following strategies:
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Skill Enhancement: Continuously update your skills in emerging technologies and methodologies in AI/ML and data science. Specializing in niche areas can make you more valuable.
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Leadership Roles: Aim for higher leadership roles such as Director of Data Strategy or Chief Data Officer, which come with increased responsibilities and higher pay.
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Industry Transition: Consider transitioning to industries that offer higher compensation for data roles, such as finance, healthcare, or tech.
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Networking and Visibility: Increase your professional visibility by speaking at conferences, publishing articles, or participating in industry forums. Networking can open doors to higher-paying opportunities.
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Negotiation Skills: Improve your negotiation skills to better advocate for salary increases during performance reviews or when offered new positions.
Educational Requirements for a Data Strategy Lead
Most Data Strategy Lead positions require at least a bachelor's degree in a relevant field such as Computer Science, Data Science, Statistics, or Business Administration. However, a master's degree or MBA is often preferred, especially for roles that involve strategic decision-making and leadership. Advanced degrees can provide a deeper understanding of data analytics, business strategy, and management, which are crucial for this role.
Helpful Certifications for a Data Strategy Lead
While not always mandatory, certain certifications can enhance your qualifications and demonstrate expertise:
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Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
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Google Professional Data Engineer: Demonstrates proficiency in designing and managing data solutions on Google Cloud.
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AWS Certified Big Data – Specialty: Focuses on data analytics and big data solutions on the AWS platform.
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SAS Certified Data Scientist: Covers data manipulation, predictive modeling, and machine learning.
These certifications can help differentiate you from other candidates and may lead to better job opportunities and salary prospects.
Experience Required for a Data Strategy Lead
Typically, a Data Strategy Lead position requires 5 to 10 years of experience in data-related roles. This experience should include hands-on work with data analysis, machine learning, and data management. Leadership experience is also crucial, as the role involves guiding teams and making strategic decisions. Experience in specific industries can be beneficial, as it provides context and understanding of industry-specific data challenges and opportunities.
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