Senior Data Scientist

Brightspeed•Charlotte, NC

7d•Hybrid

About The Position

We are currently looking for a Senior Data Scientist to join our Finance, Strategy & Transformation team at Brightspeed. You will be responsible for developing AI and ML solutions to drive improved business performance and efficiency across domains. You will lead end-to-end AI/ML projects from understanding business needs to data preparation, model development, solution deployment, and post-production monitoring. You will dissect and solve complex business problems using analytical and quantitative approaches to identify patterns and correlations in large complex data sets. You will integrate and curate data from a wide range of internal and external sources to develop rich datasets for predictive & prescriptive modeling as well as machine learning. You will define and implement best practices to generate accurate reports, visualizations & dashboards to explain results simply and succinctly to technical and non-technical users. You will create models for visual recognition, processing of natural language that analyze complex data to make predictions or decisions, mimicking human intelligence. You will identify the most effective model architecture and parameters to drive accuracy and performance. You will liaise with stakeholders to understand their needs and concerns and develop concise analytics to provide actionable insights to influence strategy and performance. You will build partnerships, share knowledge, and deliver valuable predictive insights to inform strategic decisions, all the while highlighting potential risks and opportunities.

Requirements

5+ years of experience of building AI and/or machine learning models for business application
3+ years of hands-on experience with training, fine tuning, evaluating, and deploying models in production
3+ years of experience with data lake and cloud services, preferably GCP
Bachelor’s degree or higher in Computer Science, Operations Research, Statistics, Mathematics or related field.
Deep expertise in machine learning, neural networks, computer vision, large language models, natural language processing or similar discipline
Demonstrated experience in algorithm selection, model training, feature engineering, fine-tuning performance and implementation
Proficiency in Python and key data science libraries, including Pandas, NumPy, Scikit-learn, Matplotlib and/or Seaborn
Strong capabilities in SQL and experience working with SQL query engines
Expertise in Agile methodology for product and software development
Experience with leveraging Data Science and AI to drive business optimization
Ability to navigate ambiguous problem contexts and apply critical thinking to identify/diagnose problems and solve with simple, logical solutions
Excellent quantitative skills and data-driven decision-making capabilities
Ability to clearly articulate insights (verbal and written)
Ability to effectively communicate technical and non-technical information and concepts to all levels or organization
Ability to work effectively in a fast-paced, dynamic environment, managing multiple priorities and deadlines simultaneously

Nice To Haves

Master’s degree strongly preferred.
Data Science or AI certifications
Experience with Data Visualization tools such as Power BI
Relevant Telecom experience
2+ years of experience with the design, deployment and evaluation of AI agents and orchestration

Responsibilities

Lead end-to-end AI/ML projects from understanding business needs to data preparation, model development, solution deployment, and post-production monitoring.
Dissect and solve complex business problems using analytical and quantitative approaches to identify patterns and correlations in large complex data sets.
Integrate and curate data from a wide range of internal and external sources to develop rich datasets for predictive & prescriptive modeling as well as machine learning.
Define and implement best practices to generate accurate reports, visualizations & dashboards to explain results simply and succinctly to technical and non-technical users.
Create models for visual recognition, processing of natural language that analyze complex data to make predictions or decisions, mimicking human intelligence.
Identify the most effective model architecture and parameters to drive accuracy and performance.
Liaise with stakeholders to understand their needs and concerns and develop concise analytics to provide actionable insights to influence strategy and performance.
Build partnerships, share knowledge, and deliver valuable predictive insights to inform strategic decisions, all the while highlighting potential risks and opportunities.