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Analytics Strategy Jobs in Ohio (NOW HIRING)

The analytics engineering layer on BigQuery is healthy and fully owned, and the team actively ... Set the strategy, operating model, and priorities for the performance metrics function. * Establish ...

Work cross-functionally with commercial, analytics, operations, and product teams to execute strategic projects * Support strategic planning, reporting, and forecasting processes Qualifications:

Work cross-functionally with commercial, analytics, operations, and product teams to execute strategic projects * Support strategic planning, reporting, and forecasting processes Qualifications:

Work cross-functionally with commercial, analytics, operations, and product teams to execute strategic projects * Support strategic planning, reporting, and forecasting processes Qualifications:

Work cross-functionally with commercial, analytics, operations, and product teams to execute strategic projects * Support strategic planning, reporting, and forecasting processes Qualifications:

We are seeking a strategic and transformational Reporting & Analytics Leader to join our Sales, Credit, and Servicing Center of Excellence . This leader will be responsible for defining and executing ...

We are seeking a strategic and transformational Reporting & Analytics Leader to join our Sales, Credit, and Servicing Center of Excellence . This leader will be responsible for defining and executing ...

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Analytics Strategy information

See Ohio salary details

$51.3K

$95.9K

$142.6K

How much do analytics strategy jobs pay per year?

As of Jul 16, 2026, the average yearly pay for analytics strategy in Ohio is $95,921.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,200.00 and $128,300.00 per year, depending on experience, location, and employer.

What is the difference between Analytics Strategy vs Data Analyst?

AspectAnalytics StrategyData Analyst
Primary FocusDeveloping overall data-driven plans and long-term strategiesAnalyzing data sets to generate reports and insights
Skills & CertificationsBusiness acumen, strategic thinking, data management, often with certifications like CBIP or similarStatistical analysis, SQL, Excel, with certifications like CAP or Microsoft Data Analyst
Work EnvironmentCollaborates with leadership to align data initiatives with business goalsWorks with data sets, tools, and reporting platforms to produce insights

While both roles involve working with data, Analytics Strategy focuses on creating comprehensive plans to leverage data for business growth, whereas Data Analysts concentrate on examining data to generate specific insights and reports. Understanding these differences helps organizations assign the right responsibilities and professionals to each role.

What is an analytics strategy?

An analytics strategy is a plan that outlines how an organization uses data analysis to support decision-making and achieve business goals. For an analytics strategy role, it involves defining key metrics, selecting appropriate tools, and establishing processes for data collection, analysis, and reporting. Developing a strong strategy requires understanding business needs, data management, and analytical techniques.

What does a strategy analyst do?

A strategy analyst evaluates business data and market trends to develop strategic plans that improve company performance. They analyze financial reports, create models, and provide insights to support decision-making. Proficiency in data analysis tools and strong communication skills are essential for this role.

What is the highest paying job in data analytics?

In data analytics, senior roles such as Chief Data Officer, Data Science Director, or Analytics Executive typically have the highest salaries, often exceeding six figures annually. These positions require advanced skills in data management, strategic planning, and leadership, along with extensive experience and often relevant certifications.

What is analytics strategy?

Analytics strategy refers to the planning and implementation of processes, tools, and personnel required to collect, analyze, and use data effectively within an organization. Professionals in analytics strategy help organizations make data-driven decisions by aligning analytics initiatives with business goals. This involves identifying key metrics, selecting appropriate analytics technologies, and ensuring that data insights lead to actionable outcomes. An effective analytics strategy can improve efficiency, drive innovation, and provide a competitive advantage.

How does an Analytics Strategy professional typically collaborate with other departments within an organization?

Analytics Strategy professionals often act as a bridge between data teams and business units, working closely with departments such as marketing, finance, operations, and IT. They translate business objectives into data-driven strategies and ensure that analytics initiatives align with organizational goals. Collaboration often involves leading cross-functional meetings, understanding the specific needs of each department, and communicating insights in a clear, actionable manner. This collaborative environment helps drive adoption of analytical solutions and maximizes organizational impact.

What are the key skills and qualifications needed to thrive in Analytics Strategy, and why are they important?

To excel in Analytics Strategy, you need strong analytical thinking, data interpretation skills, and a background in business, statistics, or a related field. Expertise with data visualization tools (like Tableau or Power BI), statistical software (such as R or Python), and experience with data management systems are typically required. Strategic thinking, problem-solving, and effective communication enable professionals to translate analytical insights into actionable business recommendations. These skills are critical to inform decision-making and drive organizational growth through data-driven strategies.

Is 40 too late for data science?

For an analytics strategy role, starting a career in data science at age 40 is feasible, as many skills such as programming, statistics, and data visualization can be learned at any age. Experience in related fields and continuous learning through online courses or certifications can help transition into data science roles regardless of age.
Director of Data Analytics

Other

Medical, PTO

Posted 13 days ago


Job description

Position Overview 

Educate! is becoming more data- and technology-driven, and the performance metrics function is central to that shift. This function tracks our monitoring metrics-both operational metrics that help implementation teams run programs well, and classic monitoring of whether we are doing the right things: activities, outputs, and near-term outcomes. It works alongside, and hands off cleanly to, a separate evaluation team that owns deeper impact and causal work.

This is a build role at a pivotal moment, and you will drive two important shifts: First, transforming our current Performance Metrics team, structures, and processes to become AI-native. Second, you will sit on a cross-functional team of senior leaders to implement our predictive analytics strategy, working in partnership with our evaluation, product, implementation, and tech teams.

As our most senior data leader, the Director of Data Analytics will design and own all four pillars of Educate!'s data function: data design, data engineering and infrastructure, analytics oversight, and data collection. You will operate as a "full-stack analyst" leader: technically fluent in SQL, dbt, and cloud warehousing, while acting as a people leader and a trusted cross-functional partner to Technology, Evaluation, and Product.

Expected Impact

The specific milestones below will be calibrated with the COO, but within this role's first year, we expect:

  • First 6 months: You understand the current metrics landscape, team, and data stack, and have established the function's strategy and operating model alongside the COO. The team is structured and staffed as an AI-native team built to scale.

  • By 12 months: Implementation, product, and leadership teams utilize self-service analytics for 90% of their data needs. The analytics engineering layer on BigQuery is healthy and fully owned, and the team actively utilizes AI-native practices. You are also overseeing data architecture in alignment with the predictive analytics strategy.

What You'll Do Defining Vision and Structure for Performance Metrics Function 
  • Set the strategy, operating model, and priorities for the performance metrics function. 
  • Establish direction, standards, and expectations across the entire department. 
  • Build the function's capability: Establish team structures, develop streamlined processes, and build cross-functional forums to ensure best-in-class data systems-especially as our strategy shifts toward predictive and self-service analytics. Develop your leaders through targeted coaching, clear leveling frameworks, and cultivating a team culture of rigor and continuous learning. 
  • Build systems and standards that ensure metrics actively support implementation teams in managing day-to-day program execution. 
  • Maintain a clear boundary and clean handoff with the evaluation team, ensuring the two functions complement rather than duplicate each other's efforts. 
  • Partner with the central Tech team to ensure upstream pipelines meet necessary standards, and effectively direct the shared data engineer toward achieving those goals.
Data Engineering and Infrastructure - Build and own the technical foundation
  • Design and own Educate!'s end-to-end data architecture, encompassing ingestion, warehousing, transformation, and delivery. 
  • Stand up a modern BI stack featuring self-serve reporting and automated pipelines that local country teams can readily utilize. 
  • Define the quality bar for the analytics engineering layer (dbt and the metrics layer on BigQuery) by ensuring accurate, complete, timely, consistent, valid, and traceable data, while holding your team accountable for maintaining that standard. 
  • Bring technical judgment to direct the work, assess quality (including the ability to challenge a data model or a pipeline), and execute effectively through your team.
Data Analytics Oversight - Turn data into decisions
  • Collaborate with product, implementation, and performance metrics teams to define what gets measured and how-spanning operational metrics that support program implementation and classic monitoring of activities, outputs, and near-term outcomes.
  • Establish a function deeply grounded in self-service analytics.
  • Build the capability for the team to deploy multiple dashboards tailored to different audiences across the organization. Define and reinforce a collaborative process that scopes decisions at various levels and maps them to corresponding metrics.
  • Ensure the performance metrics team transforms data into dashboards, insights, and decision tools that implementation, product, and leadership teams genuinely utilize.
  • Raise data literacy across the organization to ensure teams actively champion and act on data rather than simply collecting it.
  • Transition analysts from manual data analysis and reporting to focusing on the semantic layer of our data systems, ensuring it is optimized for AI. Similarly, usher in a shift from the performance metrics team providing manual analysis to a model of self-service analytics complemented by robust dashboards.
  • Develop a strategy to improve frontline data usage in partnership with implementation teams, leveraging AI alongside both qualitative and quantitative data sources. The ultimate goal of this strategy is to ensure program implementation scales with consistency and quality.
Partner and Accelerate Analytics
  • Act as the senior cross-functional partner to Tech, Evaluation, and Product, and a trusted advisor to the COO.
  • Sponsor the function's contribution to the cross-functional data science workstream to help analytics move faster organization-wide.
  • Champion shared tools, standards, and ways of working that lift the whole organization's analytical capability.
Who You Are
  • You bring around 7+ years in analytics, data, or M&E roles, including several years building and leading teams. You have managed managers, not only individual contributors. 
  • You have built or substantially grown a data or analytics team, and can speak to hiring, leveling, and developing analysts and engineers. 
  • You have genuine analytics-engineering depth: you reason fluently about data models, transformations, and a metrics layer, and you are comfortable with SQL, dbt-style workflows, and a warehouse like BigQuery enough to direct a data engineer and judge pipeline quality, even if you no longer code every day. 
  • You think in indicators, not just dashboards. You can make data accurate, complete, timely, consistent, valid, and traceable. You can also monitor that quality over time and understand the distinction between monitoring and evaluation. 
  • You get teams to act on data. You are an effective cross-functional partner and a clear communicator who can make technical trade-offs understandable to non-technical audiences, including executives. 
  • You are energized by the mission - improving learning, earning, and livelihood outcomes for youth across East Africa. 
  • Fits our Five Culture Tenets (see What is Educate! About? below); Learn more by looking at Educate!'s culture deck here  

Non-Traditional Backgrounds Are Welcome
This role does not require a traditional M&E or non-profit background. We equally welcome strong analytics, data-science, or business-intelligence leaders from start-ups, social enterprises, or the private sector who can pick up the mission context quickly. What matters most is analytical depth, leadership ability, and sound judgment. If you bring those strengths from a different setting, we encourage you to apply.

What We Offer 
  • A vibrant, mission-driven environment with a supportive and fun team. 
  • Flexibility - hybrid or fully remote work, depending on location. 
  • A competitive salary based on experience, with benefits aligned to your country of hire. 
  • Meaningful learning and growth opportunities as the function and organization scale.

Application Process: Rolling basis, interviews happening soon!

Terms 
  • A vibrant, mission-driven environment with a supportive and fun team. 
  • Competitive salary based on market factors and commensurate with experience.
  • Benefits will align with the country of hire (Kenya, Uganda, Tanzania, or, Rwanda) and typically include medical and travel insurance, Learning & growth opportunities, flexibility on work hours when needed and hybrid work, paid leave plus one week of office closure over the December holidays, and more.
  • African candidates strongly preferred. 
  • We will also consider applications from exceptional candidates based outside East Africa and the UK, where we do not have a physical office. For these candidates, the role will be remote and will involve substantial travel.