Data Scientist

Acxiom•Conway, AR

30d•Onsite

About The Position

At Acxiom, we transform data into actionable insights that drive operational excellence and business value. We are seeking a Data Scientist to support reconciliation, settlement, and transaction analysis activities for a strategic client account across multiple products and vendor partners. The Data Scientist will leverage analytical methods, statistical techniques, data visualization, and business intelligence tools to identify trends, anomalies, operational risks, and opportunities for process improvement. This role partners with clients, vendor organizations, and internal stakeholders to investigate transaction discrepancies, analyze financial and operational data, provide actionable insights, and support data-driven decision-making. The ideal candidate combines strong analytical capabilities with reconciliation and financial operations knowledge and has the ability to transform complex transactional data into meaningful business recommendations that improve operational performance, reduce financial losses, and enhance the client experience. The Data Scientist is responsible for analyzing transaction, settlement, and reconciliation data to identify discrepancies, trends, root causes, risks, and opportunities for operational improvement. This role supports reconciliation and settlement operations through advanced analytics, reporting, data preparation, visualization, and insight generation. The Data Scientist collaborates with clients, vendors, Accounting, Product, Engineering, Production Support, and operational teams to understand business needs, investigate complex issues, evaluate financial impacts, and communicate analytical findings. This role applies data-driven thinking to improve reconciliation accuracy, strengthen operational controls, and drive continuous improvement initiatives. The position requires strong communication skills, analytical curiosity, and the ability to manage multiple priorities while transforming large volumes of transaction data into business value. The role serves as a key liaison between clients, vendors, and internal teams to ensure accurate settlements, timely issue resolution, meaningful reporting, and continuous operational improvement.

Requirements

Bachelor's degree in Data Science, Statistics, Mathematics, Finance, Accounting, or a related quantitative field, or equivalent experience.
Experience analyzing large transactional, financial, operational, or reconciliation datasets.
Strong analytical, critical-thinking, and problem-solving skills.
Experience applying statistical methods and data-driven analysis to business problems.
Advanced Microsoft Excel skills, including PivotTables, XLOOKUP/VLOOKUP, formulas, and data analysis techniques.
Strong SQL skills with the ability to retrieve, join, validate, and analyze data from multiple data sources.
Experience developing dashboards, visualizations, and business intelligence reporting.
Ability to identify trends, anomalies, patterns, and root causes within complex datasets.
Experience preparing, cleansing, validating, and transforming data for analysis and reporting.
Ability to leverage critical data-driven thinking and translate data into actionable insights and recommendations.
Experience evaluating financial impacts, operational risks, and performance metrics.
Strong verbal and written communication skills with the ability to present complex findings to business and technical audiences.
Experience working directly with clients, vendors, and cross-functional stakeholders.
Strong stakeholder management and relationship-building capabilities.
Experience facilitating discussions, driving issue resolution, and influencing decisions across multiple organizations.
Root cause analysis and investigative research expertise.
Knowledge of reconciliation, settlement operations, financial transactions, payments, or related business processes.
Experience with process improvement, operational analytics, and performance measurement.
Ability to balance analytical rigor with practical business needs and operational realities.
Attention to detail and time management skills with the ability to deliver high-quality work across multiple priorities and deadlines.
Experience documenting analytical findings, methodologies, processes, and business recommendations.

Nice To Haves

Familiarity with Power BI, Tableau, Python, R, or similar analytical tools preferred.
Interest in leveraging artificial intelligence and automation technologies to improve operational processes and decision-making.

Responsibilities

Analyze transaction, settlement, and reconciliation datasets to identify discrepancies, trends, anomalies, and operational risks.
Collaborate with clients, vendors, and internal stakeholders to understand business objectives, operational challenges, and reporting requirements.
Perform root cause analysis to determine drivers of financial discrepancies, processing issues, and settlement variances.
Develop and maintain dashboards, reports, scorecards, and visualizations that communicate financial and operational performance.
Apply statistical analysis and data-driven methodologies to support operational decision-making.
Evaluate transaction and settlement data to identify process inefficiencies, risk indicators, and improvement opportunities.
Investigate exception trends and provide recommendations to reduce customer friction and financial loss.
Support monthly, quarterly, and ad hoc business reviews through analytical reporting and insight generation.
Translate complex data findings into actionable recommendations for business and technical stakeholders.
Prepare, cleanse, validate, and transform data from multiple internal and external sources to support analysis and reporting.
Utilize SQL, Excel, and analytical tools to retrieve and analyze large datasets.
Partner with Product, Engineering, Accounting, and Operations teams to support issue resolution and process improvements.
Lead discussions with vendor partners regarding reconciliation findings, settlement issues, enhancement opportunities, and corrective action plans.
Present analytical findings, financial impacts, trends, and recommendations to clients, vendors, and leadership teams.
Identify opportunities for automation of reconciliation, reporting, and research activities.
Monitor key operational metrics and provide proactive recommendations based on observed trends and performance indicators.
Identify potential fraud indicators, recurring exceptions, problematic transaction patterns, and emerging operational risks.
Maintain documentation of analytical methodologies, findings, assumptions, and business recommendations.
Produce monthly reconciliation summaries, variance reporting, operational scorecards, and executive-level insights.
Support testing, implementation, and operational readiness activities for new products, vendor integrations, and system enhancements.
Promote continuous improvement through analytics, automation, artificial intelligence, and emerging technologies where appropriate.