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Director Data Science Analytics Jobs in Kansas (NOW HIRING)

$98K - $118K/yr

The team works closely with product managers, backend engineers, web engineers, data scientists, analysts, business teams, and customer-facing teams to make data accurate, timely, scalable, and easy ...

$159K - $285K/yr

... to Director of Growth and Data Science in the Experience Foundations organization. This is a ... Design and implement predictive models to analyze and anticipate user behavior, intent, and ...

... analysis-ready assets that power Life Sciences and RWE use cases. Working within the internal data ... The role blends applied data science, large language model (LLM) evaluation, and platform ...

... analysis-ready assets that power Life Sciences and RWE use cases. Working within the internal data ... The role blends applied data science, large language model (LLM) evaluation, and platform ...

... analysis or data science with demonstrated progression in technical scope and complexity * Expert-level SQL across both Snowflake and SQL Server - stored procedures, query optimization, and complex ...

Step into a high-impact role where your analytics shape real business decisions. At TreviPay, we're looking for a Directo r of Decision Science who is a data-driven risk expert who thrives on turning ...

Step into a high-impact role where your analytics shape real business decisions. At TreviPay, we're looking for a Directo r of Decision Science who is a data-driven risk expert who thrives on turning ...

... Data Science, Statistics, or a related field. * 4 to 10 years of related work experience and/or training, or an equivalent combination of education and experience. * Strong analytical skills and ...

The role blends applied data science, large language model (LLM) evaluation, prompt and workflow ... mode analysis, and ongoing quality monitoring. * Rapidly prototype and test approaches, using ...

The role blends applied data science, large language model (LLM) evaluation, prompt and workflow ... mode analysis, and ongoing quality monitoring. * Rapidly prototype and test approaches, using ...

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Director Data Science Analytics information

Is 40 too late for data science?

For a Director of Data Science Analytics, starting a career at 40 is not too late, as many professionals transition into data roles later in life. Success depends on relevant skills, experience, and continuous learning in areas like machine learning, programming, and data management. Age is less important than demonstrated expertise and adaptability in the field.

What does a director of data analytics do?

A director of data analytics oversees the development and implementation of data analysis strategies to support business goals. They lead teams of data scientists and analysts, manage data projects, and ensure the accuracy and integrity of data insights, often using tools like SQL, Python, or Tableau. This role requires strong leadership, strategic thinking, and expertise in data management and analytics techniques.

What is the salary of head of data science and analytics?

The salary for a Director of Data Science and Analytics typically ranges from $120,000 to $180,000 annually, depending on experience, industry, and location. Senior roles may also include bonuses, stock options, and other benefits, with higher compensation for those with advanced skills in machine learning, statistical analysis, and leadership.

What is the 80 20 rule in data science?

The 80/20 rule, also known as Pareto principle, suggests that roughly 80% of effects come from 20% of causes. In data science, it often means focusing on the most impactful features or data points to improve model performance efficiently, making it a useful concept for data analysis and feature selection. Understanding this rule helps data scientists prioritize efforts and optimize resources in analytics projects.
What are the most commonly searched types of Data Science Analytics jobs in Kansas? The most popular types of Data Science Analytics jobs in Kansas are:
What cities in Kansas are hiring for Director Data Science Analytics jobs? Cities in Kansas with the most Director Data Science Analytics job openings:

Staff Software Engineer, Data Delivery

StackAdapt

On-site

$98K - $118K/yr

Other

This job post has expired 2 days ago. Applications are no longer accepted.


Job description

About the team

The Data Delivery team builds the systems that help StackAdapt customers and internal teams understand campaign performance.

We process, organize, and serve large volumes of campaign and marketing data so it can be used reliably across customer-facing dashboards, reporting, billing, planning, campaign pacing, measurement, exports, and internal analytics.

Our work turns raw activity - such as impressions, clicks, conversions, spend, pacing, audience reach, creative performance, and cross-channel engagement - into accurate and actionable insights.

The team works closely with product managers, backend engineers, web engineers, data scientists, analysts, business teams, and customer-facing teams to make data accurate, timely, scalable, and easy to use.

Why this role matters

StackAdapt is expanding into the next generation of AI-powered advertising and marketing execution. As the platform grows across media, email, social, and emerging AI-powered channels, customers need a trusted view of performance across the full customer journey.

The Data Delivery team is at the forefront of making this possible. We build the reporting, measurement, planning, billing, API, export, and data-serving systems that help customers trust the data, understand performance, and optimize campaigns.

As a Staff Software Engineer I on Data Delivery, you will lead complex technical initiatives across backend systems, with a focus on measurement and planning. You will act as a project and domain DRI for this area: translating product requirements into technical requirements, clarifying feasibility and trade-offs, shaping milestones, identifying risks, and keeping execution moving.

You will partner closely with product, engineering, and engineering management to recommend technical options, push back on unrealistic plans when needed, and help the team make sound decisions. Your work will help build the technical foundation for reliable customer-facing insights and make new product capabilities easier to launch and scale.

To learn more about StackAdapt's broader platform vision, watch Yang Han discuss the evolution of StackAdapt's AI-powered advertising and marketing platform: How AI Advertising Platform StackAdapt Connects Marketers With Agencies - CTO Yang Han

What you'll be doing
  • Domain ownership: Act as a project and domain DRI for measurement and planning initiatives within Data Delivery.
  • Technical planning: Translate product requirements into technical requirements, clarify feasibility and trade-offs, shape milestones, and identify risks early.
  • Execution leadership: Keep complex initiatives moving by unblocking decisions, coordinating across teams, and giving engineering leadership clear options and recommendations.
  • Scalable data systems: Build reliable systems that process, organize, and serve large volumes of campaign and marketing data across StackAdapt.
  • Customer-facing impact: Power reporting, measurement, planning, billing, pacing, exports, APIs, and analytics that customers and internal teams depend on.
  • System design: Make thoughtful technical decisions that balance correctness, reliability, latency, freshness, cost, and long-term maintainability.
  • Cross-functional partnership: Work closely with product, engineering, data science, analytics, and business teams to turn product goals into strong technical solutions.
  • Operational excellence: Improve monitoring, testing, data quality, incident response, and documentation so our systems are easier to trust and operate.
  • Technical mentorship: Support engineers through design reviews, code reviews, technical guidance, and clear communication of trade-offs.
What you'll bring
  • Backend and data systems experience: Strong experience building scalable services, distributed systems, data platforms, or data-intensive applications.
  • Project leadership: Experience leading complex technical projects with ambiguous requirements, multiple stakeholders, and meaningful trade-offs.
  • System design depth: Strong judgment across APIs, data pipelines, databases, distributed systems, observability, reliability, and operational ownership.
  • Data quality mindset: Ability to reason about correctness, freshness, completeness, consistency, cost efficiency, and customer trust.
  • Product judgment: Interest in building systems that support customer-facing reporting, measurement, planning, optimization, and analytics.
  • Technical communication: Ability to explain decisions clearly, align stakeholders, and document important trade-offs.
  • Mentorship: Experience helping other engineers grow and raising the technical bar of a team.
  • Technical stack: Strong programming skills; experience with Golang and technologies such as Kafka, TiDB, Redshift, Vitess, Iceberg, StarRocks, or Trino is a plus.
  • Domain experience: Experience in adtech, marketing technology, reporting, analytics, billing, attribution, planning, or high-volume event processing is a plus.
What success looks like

You will help Data Delivery build trusted, scalable, and efficient data systems that customers and internal teams rely on to understand performance and make better decisions.

In practice, this means:

  • Measurement and planning initiatives have clear technical direction, realistic milestones, and strong execution across teams.
  • Customers can trust the data they use to evaluate and optimize campaigns.
  • Core data systems are more reliable, scalable, and easier to build on.
  • New metrics, datasets, APIs, exports, and reporting capabilities can launch faster and with greater confidence.
  • Product and engineering teams can build new advertising, marketing, measurement, and AI-powered capabilities more easily.
  • The team makes better technical decisions because trade-offs are clearly understood and communicated.
  • Engineers around you grow through your mentorship, guidance, and example.
  • Data Delivery helps StackAdapt scale new product opportunities by giving customers a trusted view of performance across channels and the customer journey.

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