AI ML Data Expert

Description -

Job Summary

• An AI/ML Data Expert is responsible for designing, developing, and deploying machine learning models and AI-driven solutions that enhance business intelligence, automate processes, and generate predictive insights. This role bridges the gap between raw data and actionable intelligence, requiring deep technical expertise and strategic thinking.

• This role is responsible for data collection procedures, including accurate and relevant data for machine learning models, extracting and analyzing data from the primary and secondary database. The role ensures data integrity and compliance by performing data cleansing and data validations. The role performs root-cause analysis and recommends or executes corrective actions when data related system problems occur. The role provides quantitative rationale for executing customer and product strategies and tactics. The role applies advanced subject matter knowledge to solve complex business issues and is regarded as a subject matter expert.

Responsibilities

AI/ML Model Development

•Design and implement machine learning and deep learning models.

•Conduct model validation, testing, and refinement.

•Apply NLP, computer vision, and predictive analytics for advanced insights.

•Develop AI-driven solutions for automation and decision support.

Data Engineering & Analysis

•Build scalable data pipelines and ETL processes.

•Ensure data quality, integrity, and consistency.

•Collaborate with stakeholders to understand data requirements.

•Conduct exploratory data analysis and feature engineering.

• Leads one or more project teams of other data engineers for all stages of design and development for complex, secure and performant data solutions and models, including design, analysis, coding, testing, and integration of structured/unstructured data.

• Reviews and evaluates designs and project activities for compliance with architecture, security and quality guidelines and standards; provides tangible feedback to improve product quality and mitigate failure risk.

• Provides domain-specific expertise and overall data systems leadership and perspective to cross-organization projects, programs, and activities.

• Drives innovation and integration of new technologies into projects and activities in the big data space.

• Collaborates and communicates with project team regarding project progress and issue resolution.

• Represents the data engineering team for all phases of larger and more-complex development projects.

• Assists in the coaching and training of business analytics solution users to enhance business decision-making capability.

• Ensures and maintains a high level of data integrity by using tools to monitor and mass update data changes.

• Builds and manages relationships throughout the organization.

• Provides guidance and mentoring to less experienced staff members.

**Education & Experience Recommended**

• Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, Statistics/ Mathematics, or any other related discipline or commensurate work experience or demonstrated competence.

• Typically has 7-10 years of work experience, preferably in data analytics, data engineering, data modeling, or a related field.

• Proficiency in Python, R, SQL, Java.

• Experience with ML frameworks: TensorFlow, PyTorch, Scikit-learn.

• Familiarity with cloud platforms and big data tools (e.g., Spark, Hadoop).

• Strong grasp of model tuning, algorithm optimization, and data preprocessing.

Soft Skills

• Analytical thinking and problem-solving.

• Effective communication and teamwork.

• Passion for innovation and continuous learning.

Preferred Certifications

• Programming Language/s Certification (SQL, Python, or similar)

Knowledge & Skills

• Agile Methodology

• Amazon Web Services

• Apache Hadoop

• Apache Kafka

• Apache Spark

• Big Data

• Computer Science

• Data Analysis

• Data Engineering

• Data Modeling

• Data Pipelines

• Data Warehousing

• Extract Transform Load (ETL)

• Java (Programming Language)

• Machine Learning

• Microsoft Azure

• Python (Programming Language)

• Scala (Programming Language)

• Scalability

• SQL (Programming Language)

Cross-Org Skills

• Effective Communication

• Results Orientation

• Learning Agility

• Digital Fluency

• Customer Centricity

Impact & Scope

• Impacts function and leads and/or provides expertise to functional project teams and may participate in cross-functional initiatives.

Complexity

• Works on complex problems where analysis of situations or data requires an in-depth evaluation of multiple factors.

Disclaimer

• This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management.