Job Description

Title: Data Strategist

Location: Remote

About Agero:Wherever drivers go, we’re leading the way. Agero’s mission is to rethink the vehicle ownership experience through a powerful combination of passionate people and data-driven technology, strengthening our clients’ relationships with their customers. As the #1 B2B, white-label provider of digital driver assistance services, we’re pushing the industry in a new direction, taking manual processes, and redefining them as digital, transparent, and connected. This includes: an industry-leading dispatch management platform powered by Swoop; comprehensive accident management services; knowledgeable consumer affairs and connected vehicle capabilities; and a growing marketplace of services, discounts and support enabled by a robust partner ecosystem. The company has over 150 million vehicle coverage points in partnership with leading automobile manufacturers, insurance carriers and many others. Managing one of the largest national networks of service providers, Agero responds to approximately 12 million service events annually. Agero, a member company of The Cross Country Group, is headquartered in Medford, Mass., with operations throughout North America. To learn more, visit

Job Summary:

Agero is currently seeking a talented Data Strategist to join our team. This role provides an exciting opportunity not only to harness the potential of large datasets to drive business growth and develop strategic insights but also to shape your career path towards becoming a key decision-maker. We are passionate about fostering a data-centric culture and encourage innovative thinking. If you are someone who thrives on uncovering insights from numbers and influencing business decisions through data, we would love to hear from you.

Key Outcomes:

  • Design, develop, and implement predictive, descriptive, and prescriptive models that could drive strategic decisions in various aspects of the business.
  • Analyze complex datasets, identify patterns, trends, anomalies, and derive actionable insights.
  • Collaborate with cross-functional teams including Data Engineers, Business Analysts, Product Managers, and other stakeholders to identify opportunities for leveraging company data to drive business solutions.
  • Present findings and data-driven recommendations to non-technical stakeholders and executive leadership.
  • Ensure data accuracy and consistent reporting by designing and creating optimal processes and procedures for analytics employees to follow.
  • Develop and implement data collection methodologies and data quality assurance processes.
  • Collect, clean, and preprocess large volumes of structured and unstructured data from various sources.
  • Create data visualizations, reports, and dashboards to effectively communicate findings and recommendations to stakeholders.
  • Stay updated with the latest advancements and trends in data science and analytics.


  • Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or a technical field.
  • Proficient in Python, R, SQL, and data visualization tools such as Tableau or PowerBI.
  • Knowledge of data visualization tools, such as Tableau, Power BI, or D3.js.
  • Experience in statistical techniques such as Regression, Hypothesis Testing, Natural Language Processing, Machine Learning algorithms.
  • Strong problem-solving skills and the ability to translate business requirements into analytical solutions.
  • Excellent communication skills to present findings and insights to non-technical stakeholders.
  • Attention to detail and the ability to work independently as well as part of a team.
  • Proven ability to comprehend business strategies and objectives, translate business needs into analytical projects, and derive actionable insights to positively impact business performance.

Preferred Qualifications:

  • Experience with big data technologies and distributed computing frameworks, such as Hadoop or Spark.
  • Knowledge of natural language processing (NLP) and text mining techniques.
  • Experience with cloud platforms, such as AWS or Azure.
  • Familiarity with data engineering processes, including data extraction, transformation, and loading (ETL).
  • Previous experience in a technical role or experience at a top-tier professional services or leading technology company.