Data & Analytics Business Partner

CONA Services•Dallas, TX

About The Position

The Advanced Analytics Translator serves as an integrator between technical and business teams on Advanced Analytics projects. The role combines data and analytics knowledge with business acumen to define problems analytics can address, guide technical teams in developing analytics-driven solutions, and embed those solutions into business operations. The position connects data engineers, architects, and scientists with operational stakeholders across marketing, supply chain, manufacturing, risk, and frontline functions. It leads cross-functional project work from requirements and feasibility through execution and user acceptance, evaluates analytical methods and outputs, and supports deployment and ongoing maintenance of solutions. The role also analyzes data, communicates project outcomes to varied audiences, builds organizational awareness of Advanced Analytics, and applies industry knowledge to business needs.

Requirements

Bachelor’s degree in a relevant field such as Engineering, Computer Science, Mathematics, or Statistics; the posting also lists Business, Analytics, Information Systems, or a related field.
At least 3 years of work experience in a data-centric business environment, including experience in analytics, business intelligence, data translation, consulting, or another data-driven environment.
Strong business and operational knowledge and business acumen, including the ability to understand processes, identify opportunities, and translate business needs into data, analytics, and technology requirements.
Strong consultative communication, facilitation, and stakeholder-management skills, including the ability to explain technical concepts and analytical findings to non-technical audiences.
Proficiency in SQL and experience with analytics and visualization tools such as Power BI, ThoughtSpot, Python, or similar platforms.
Knowledge of statistics, Big Data, machine learning, data science, and IoT.
Experience analyzing large and complex datasets to identify trends, opportunities, risks, and actionable business insights.
Working knowledge of statistics, predictive analytics, machine learning, and data science concepts, including the ability to evaluate and communicate analytical approaches and results.
Familiarity with predictive statistical models, cloud computing, consumer and syndicated data, and marketing practices.
Familiarity with data management concepts, including data modeling, data quality, governance, and cloud-based data platforms.
Comfort and intellectual curiosity working with large datasets, and ability to involve relevant team members to address identified and emerging needs.

Nice To Haves

Graduate or advanced degree preferred.
Strong business and operational knowledge gained from working directly with operations is desirable.
Familiarity with Advanced Analytics tools such as Scala, R, Python, SQL, Matlab, SAS, SPSS, Minitab, Hive, Hadoop, Pig, Tableau, or Spotfire.

Responsibilities

Connect technical teams and business and operational stakeholders to identify opportunities, define requirements, and deliver data-driven solutions.
Lead cross-functional teams in understanding business and functional requirements for data science projects, including scoping and structuring data-related activities.
Work with data engineers and data scientists to understand data requirements and solve problems related to appropriate data structures.
Explain the advantages and disadvantages of analytics approaches and advanced algorithms in accessible terms, and conduct quality control on analytical outputs with targeted recommendations for improvement.
Ensure Advanced Analytics solutions are fully deployed and operated by product owners, with follow-up to sustain solutions and coordinate improvements and maintenance with technical teams.
Conduct project reviews, feasibility assessments, prioritization, initiation, execution, and user acceptance for Advanced Analytics project work.
Measure and communicate Advanced Analytics project outcomes to audiences at different organizational levels.
Develop or apply deep industry expertise and understand the broader state of analytics to apply techniques across industries.
Promote Advanced Analytics within the organization and build awareness of its benefits.
Evaluate mathematical and statistical models and methodologies used by Advanced Analytics technical teams, make factual recommendations, and ensure outputs meet business needs.
Analyze data to identify trends, patterns, risks, and opportunities, and provide actionable insights and recommendations for data-driven decision-making.