Operations Data Scientist

Electronic Transaction Consultants Corporation; United States; On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Paid days off

Health and Dental plans

Retirement plans

EFAP (Employee and Family Assistance)

Job summary

Electronic Transaction Consultants Corporation is hiring an Operations Data Scientist to apply data science, statistics, and ML to enhance system reliability and operational performance. You will analyze large volumes of data from operations, maintenance, incidents, and logs to detect trends and predict failures.

You will develop predictive capabilities to identify issues earlier, improve maintenance strategies, and reduce service impacts, collaborating with Support, Development, and Operations

Qualifications

• Proficiency in Python or R for data analysis and modeling.
• Strong SQL skills and ability to query/validate relational data.
• Solid foundation in statistics, math and data analysis.
• Experience with predictive modeling, anomaly detection, and ML techniques.
• Experience handling large/complex datasets.
• Familiarity with big data stacks (Hadoop/Spark/Hive).
• Experience with data visualization tools like Tableau/Power BI/Matplotlib.
• Ability to translate data insights into actionable recommendations.
• Strong analytical, problem-solving, and communication skills.
• Interest in production applications and system reliability.

Responsibilities

• Analyze large operational datasets to identify trends and indicators of potential failures.
• Develop and refine predictive models, rules, thresholds, and analytical methods.
• Apply statistical analysis, anomaly detection, time-series analysis, and ML techniques.
• Evaluate predictive results against failures and field results to improve accuracy.
• Expand predictive analytics and maintenance capabilities across projects.
• Develop Python or R-based data analysis, automation, and modeling solutions.
• Use SQL to query and analyze data from relational databases.
• Work with big data technologies to support analytical use cases.
• Create automated reporting, datasets, visualizations for decision-making.
• Collaborate with technical teams to understand applications and data pipelines.
• Use logs and metrics to support troubleshooting and root cause analysis.
• Participate in testing/validation of analytical solutions.
• Identify opportunities to improve system reliability and data quality.

Skills

Python

R

SQL

Statistics

Predictive Modeling

Big Data

Hadoop / Spark / Hive

Data Visualization

Communication

Education

Bachelor's degree in Data Science, CS, Stats, Math, Engineering or related field

Tools

Tableau

Power BI

Matplotlib

Job description

Overview

The Operations Data Scientist applies data science, statistical analysis, predictive modeling, and automation to improve system reliability and operational performance. This role analyzes large volumes of system, maintenance, incident, alarm, and operational data to identify trends, anomalies, and indicators of potential failures.

The role will develop predictive capabilities that allow teams to identify issues earlier, improve maintenance strategies, and reduce service impacts. This position will also work closely with Technical Support, Development, and Operations to understand the applications and systems generating the data and support the implementation of analytical solutions into production environments.

Responsibilities

• Analyze large and complex operational datasets to identify trends, anomalies, recurring issues, and indicators of potential failures.
• Develop and refine predictive models, rules, thresholds, and analytical methods.
• Apply statistical analysis, anomaly detection, time-series analysis, predictive modeling, and machine learning techniques where appropriate.
• Evaluate predictive results against actual failures, incidents, maintenance activities, and field results to measure effectiveness and improve accuracy.
• Identify opportunities to expand predictive analytics and predictive maintenance capabilities across customer projects.
• Develop Python or R-based solutions for data analysis, automation, and modeling.
• Use SQL to query, combine, validate, and analyze data from relational databases.
• Work with large-scale datasets and big data technologies to support analytical and predictive use cases.
• Develop automated reporting, datasets, visualizations, and analytical outputs to support operational and technical decision-making.
• Partner with technical teams to understand application behavior, system architecture, integrations, and data pipelines.
• Use application logs, database information, system metrics, and operational data to support troubleshooting and root cause analysis.
• Participate in testing and validation of analytical and technical solutions.
• Identify opportunities to improve system reliability, data quality, operational efficiency, and automation.
• Communicate analytical findings and recommendations clearly to technical and non-technical stakeholders.

This list of responsibilities might not cover everything you'll end up doing.

Qualifications

Required Qualifications

• Proficiency in statistical programming languages such as Python or R.
• Strong SQL skills and experience querying and analyzing relational databases.
• Strong foundation in statistics, mathematics, and data analysis.
• Experience with predictive modeling, statistical analysis, anomaly detection, and machine learning techniques.
• Experience working with large and complex datasets.
• Experience with big data technologies such as Hadoop, Spark, Hive, or similar platforms.
• Familiarity with data visualization tools such as Tableau, Power BI, Matplotlib, or similar technologies.
• Ability to analyze complex datasets and translate findings into actionable recommendations.
• Strong analytical, problem-solving, and critical-thinking skills.
• Strong technical aptitude and interest in understanding production applications and systems.
• Excellent communication skills with the ability to present technical and analytical findings to technical and non-technical stakeholders.

Preferred Qualifications

• Experience with predictive maintenance, reliability analytics, anomaly detection, or operational data.
• Experience with Linux and production application environments.
• Familiarity with Docker and containerized applications.
• Familiarity with Git or similar source control tools.
• Experience with PostgreSQL or Oracle.
• Familiarity with ELK, Kafka, ActiveMQ, or similar logging and messaging technologies.
• Familiarity with APIs and system integrations.
• Familiarity with Java-based applications or other enterprise application technologies.
• Experience supporting analytical solutions in production environments.
• Experience developing automated reporting or data-processing solutions.

Education and Experience Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Technology, or a related technical field preferred. Equivalent professional experience may be considered in lieu of a degree.

Experience in data science, predictive analytics, statistical analysis, big data, operational analytics, automation, or a related technical discipline preferred.

Core Competencies Data science, predictive analytics, statistical analysis, Python or R, SQL, big data, anomaly detection, automation, technical problem solving, system reliability, continuous improvement, cross-functional collaboration, and technical communication.

Benefits

We offer a Total Rewards plan designed with you and your family’s health and wellness in mind that includes:

• Paid days off (i.e. vacation, sick days, bereavement leave)
• Health and Dental plans
• Retirement plans
• Employee and Family Assistance Program (EFAP)
• Employee referral program

We welcome applicants from all backgrounds, regardless of race, color, religion, sex, veteran status, sexual orientation, gender identity, national origin, age, or disability or any other protected characteristics in accordance with applicable federal, state/provincial, and local laws. We’re committed to creating a workplace where everyone feels valued and respected.

We appreciate all responses and will acknowledge only those being considered for an interview.

We respectfully request no calls or unsolicited resumes from Agencies.