Data & Analytics Business Partner

General Purpose

The Advanced Analytics Translator is expected to play the role of an integrator between the technical and business roles in an Advanced Analytics project, and be proficient across Data, Analytics, and business acumen. They help define business problems that analytics can help solve, guide technical teams in the creation of analytics-driven solutions to these problems, and embed solutions into business operations.

Duties and Responsibilities

• Bridging the technical expertise of data engineers, architects, and scientists with the operational expertise of marketing, supply chain, manufacturing, risk, and frontline functions. Connecting technical teams (data engineering, scientist) with business and operational stakeholders to identify opportunities, define requirements, and deliver data-driven solutions that address key business needs.
• Lead cross-functional teams to ensure proper understanding of business/functional requirements for data science projects, including the scoping and structuring of data related activities
• Work with data engineers and data scientists to understand data requirements and problem solve on best practice data structures.
• Understand pros and cons of different analytics approaches, explain advanced algorithms, e.g., econometrics, driver regressions, machine learning etc. in simple terms and perform quality control on analytical outputs, providing targeted input and improvements to algorithms chosen
• Ensure that the Advanced Analytics solutions developed are deployed and operated in their totality by product owners, with the appropriate follow-up to sustain them, channeling improvements, and maintenance with the technical team.
• Conduct project reviews, feasibility, prioritization, initiation, execution, and user acceptance for all project work related to advanced analytics
• Measure and communicate the outcomes of the Advanced Analytics projects to different levels of audiences
• Develop or have deep industry expertise and understand current state of analytics more broadly to be able to apply techniques from across industries
• Act as an ambassador for Advanced Analytics in the organization, creating awareness of the benefits the area brings to the company.
• Evaluate the multiple mathematical and statistical models and methodologies applied by the technical roles of Advanced Analytics to provide factual recommendations and ensure the outputs fulfill the business’ needs.
• Conduct data analysis to identify trends, patterns, risks, and opportunities, providing actionable insights and recommendations that enable data-driven decision-making across the business

Qualifications

• Bachelor’s degree in relevant field: Engineering, Computer science, Mathematics, Statistics. Graduate Degree preferred. Bachelor’s degree in Business, Analytics, Engineering, Computer Science, Information Systems, Mathematics, Statistics, or a related field. Advanced degree preferred
• 3 plus years of work experience required working in a data-centric business environment. 3+ years of experience in analytics, business intelligence, data translation, consulting, or a data-driven business environment
• Strong business and operational knowledge, desirably from working directly with the operations. Strong business acumen with the ability to understand business processes, identify opportunities, and translate business needs into data,analytics, and technology requirements
• Strong consultative communication skills, preferably diagnosing data to develop successful growth strategies with clients. Strong communication, facilitation, and stakeholder management skills, with the ability to explain technical concepts and analytical findings to non-technical audiences
• Familiarity with Advanced Analytics tools such as: Scala, R, Python, SQL, Matlab, SAS, SPSS, Minitab, Hive, Hadoop, Pig, Tableau, Spotfire, etc Proficiency in SQL and experience using analytics and visualization tools such as Power BI,
• ThoughtSpot, Python, or similar platforms
• Knowledge in Statistics, Big Data, Machine Learning, Data Science, 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, with the ability to evaluate and communicate analytical approaches and results
• Familiarity with predictive statistical models, machine learning, cloud computing, consumer and syndicated data, marketing practices etc. Familiarity with data management concepts, including data modeling, data quality, governance, and cloud-based data platforms
• Proven comfort and an intellectual curiosity for working with large sets of data, pulling in relevant team members to address identified and sometimes undiscovered needs