Data Scientist / Machine Learning Engineer (Generative AI Focus)

Strategic Staffing Solutions; Charlotte (NC); Hybrid; USD 90,000 - 120,000; Full time

Job summary

Strategic Staffing Solutions is seeking a full-time Data Scientist / Machine Learning Engineer with a focus on Generative AI. This hybrid role involves advanced analytics and the development of AI solutions across various business functions. The ideal candidate will possess strong analytical skills and the ability to manage the full lifecycle of data science projects, collaborating with stakeholders to drive innovation.

The position is located in Charlotte, NC but may consider other locations like Irving, TX or Boston, MA. The role requires proficiency in SQL, Python/Java, and experience with machine learning techniques.

Qualifications

• Strong SQL and data analysis skills.
• Experience working with structured and semi-structured datasets.
• Proficiency in Python or Java for data science and machine learning.
• Hands-on experience with machine learning frameworks.
• Experience integrating Gen AI capabilities into analytical processes.

Responsibilities

• Perform in-depth data analysis and exploration using SQL.
• Work with large, complex datasets ensuring data quality.
• Design, develop, and implement scalable solutions with Python or Java.
• Communicate insights through visualizations, reports, and presentations.
• Partner closely with engineering and business stakeholders.

Skills

SQL

Data analysis

Python

Java

Machine learning framework

Generative AI

Tools

NumPy

SciPy

Matplotlib

Scikit-learn

Job description

Job Title

Data Scientist / Machine Learning Engineer (Generative AI Focus)

Contract Length

12+ Months

Schedule

Hybrid schedule 3 days per week onsite / 2 remote

Location

Charlotte, NC / Irving, TX / Boston, MA

Reference Number

246769

Overview

We are seeking a highly motivated Data Scientist / Machine Learning Engineer to build advanced analytics and Generative AI solutions across multiple business functions. This role combines strong data analysis capabilities with machine learning and emerging Gen AI techniques to drive business insights, automation, and innovation.

The ideal candidate is hands‑on, analytical, and comfortable owning the full lifecycle of data science solutions—from problem definition through model development and deployment—while collaborating closely with engineering and business stakeholders.

Key Responsibilities

• Perform in-depth data analysis and exploration using SQL and statistical techniques to uncover patterns, solve business problems, and support data‑driven decision‑making.
• Work with large, complex datasets while ensuring data quality, integrity, and usability.
• Design, develop, and implement scalable solutions using Python or Java.
• Utilize data science and machine learning libraries such as NumPy, SciPy, Matplotlib, and Scikit‑learn.
• Build reusable pipelines for data processing, feature engineering, and model evaluation.
• Develop and evaluate machine learning models, including tree‑based and ensemble algorithms such as Random Forest and XGBoost.
• Assess model performance, tune hyperparameters, and ensure models meet business and technical requirements.
• Apply AI‑assisted techniques to enhance productivity and insights.
• Craft effective prompts using Gemini or similar generative AI models to support data exploration, feature generation, analysis, and summarization.
• Communicate insights through visualizations, reports, and presentations.
• Translate complex technical findings into actionable business recommendations.
• Partner closely with engineering teams for implementation and business stakeholders to ensure alignment with strategic objectives.

Required Qualifications

• Strong SQL and data analysis skills.
• Experience working with structured and semi‑structured datasets.
• Proficiency in Python or Java for data science, machine learning, and analytical workloads.
• Hands‑on experience with machine learning frameworks and model development.
• Experience building, training, and evaluating predictive models in production or near‑production environments.
• Ability to work independently and own initiatives end‑to‑end, from problem definition and requirements gathering through solution delivery and validation.
• Experience using generative AI models to augment analytical workflows.
• Familiarity with prompt engineering.
• Experience leveraging large language models (LLMs) for automation and analytical tasks.
• Experience integrating Gen AI capabilities into analytical processes.

Generative AI Focus

• Develop and deploy Gen AI solutions that enhance productivity, automate workflows, and generate AI‑driven business insights.
• Apply foundational knowledge of Gen AI concepts, tools, and use cases.
• Experience with large language models (LLMs), prompt engineering, or AI‑assisted analytics.
• Strong interest in emerging AI technologies and a willingness to continuously learn and apply new Gen AI innovations.

Preferred Qualifications

• Experience working in financial services, banking, or capital markets environments.
• Experience in data‑driven or risk‑focused domains.
• Familiarity with cloud platforms.
• Experience with data engineering pipelines.
• Familiarity with model deployment frameworks.
• Exposure to big data technologies.
• Experience with distributed computing environments.
• Exposure to real‑time analytics environments.

Ideal Candidate Profile

• Self‑driven data professional with strong analytical and problem‑solving skills.
• Combines practical machine learning expertise with emerging AI capabilities.
• Comfortable navigating ambiguous problems and translating business needs into technical solutions.
• Capable of delivering measurable business outcomes.
• Strong communication skills with both technical and non‑technical stakeholders.
• Passionate about applying traditional machine learning and modern Generative AI techniques to solve complex business challenges.