Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Analyze and handle extensive structured and unstructured datasets utilizing SQL tools, APIs, and automated preprocessing workflows.

• Create, implement, and enhance predictive and statistical models tailored for enterprise marketing applications.

• Develop and oversee automated workflows for data transformation, cleansing, validation, and preprocessing within MLOps frameworks.

• Establish statistical evaluation metrics, loss functions, KPIs, cross-validation methods, and drift detection systems.

• Design analytical dashboards using Tableau and create interactive prototypes in Streamlit.

• Convey AI/ML methodologies, model behaviors, limitations, and insights to executive, technical, and business stakeholders.

• Convert ambiguous business and analytical challenges into technical specifications and AI product roadmaps.

• Manage AI feature backlogs with JIRA and facilitate iterative co-design and testing alongside cross-functional stakeholders.

• Examine production trends, system telemetry, performance drift, and outcome metrics.

• Lead strategic planning and prioritization for AI solutions within agile frameworks.

• Apply statistical theory, machine learning, NLP, Transformer architectures, and reinforcement learning throughout the AI/ML lifecycle.

• Review scientific literature and keep abreast of emerging AI research.

• Formulate and propose data-driven AI solutions that align with operational and revenue goals.

• Supervise model training, recalibration, drift mitigation, continuous improvement, registry management, and production monitoring.

• Develop production-quality Python AI/ML applications and model-serving APIs.

• Execute containerized deployments utilizing Docker or Podman on Kubernetes and OpenShift.

⛳️ Requirements

• Master's degree (U.S. or foreign equivalent) in Computer Science, Information Systems, Information Management, or a related field, along with two (2) years of experience in the job offered or a related role, OR a Bachelor's degree (U.S. or foreign equivalent) in the same fields with four (4) years of experience in the job offered or a related role.

• Two (2) years of experience independently designing and developing end-to-end AI or machine learning applications.

• Proven experience in translating vague business requirements into technical specifications.

• Demonstrated experience in designing UI/UX workflows and dashboards using Pencil, Tableau, or similar tools.

• Experience in building interactive web application prototypes using Streamlit.

• Proficiency in engineering scalable back-end model-serving infrastructure.

• Experience leading AI product lifecycles from conception to deployment and managing AI/ML feature backlogs using JIRA.

• Knowledge in applying NLP and deep learning techniques using Transformer architectures, Transfer Learning, and Semantic Search/Information Retrieval.

• Familiarity with NLTK, gensim, and spaCy.

• Proficient in developing predictive models with XGBoost, LightGBM, CatBoost, PyMC, and PyTorch Geometric.

• Experience with reinforcement learning, Gymnasium, and Ray.

• Hands-on Python development experience using Scikit-learn, PyTorch, and TensorFlow.

• Ability to integrate external data and services via APIs, including Google Suite APIs.

• Experience with NoSQL or high-dimensional data stores and extensive SQL database management.

• Familiarity with PostgreSQL, PL/SQL (Oracle), and Spark SQL.

• Experience in operationalizing and scaling ML models using GitLab or GitHub, Kubeflow/MLflow, Docker or Podman, Kubernetes, and OpenShift.

• Proficient in conveying complex AI concepts and model performance to technical and executive audiences using Tableau.

• Experience developing data science and AI solutions in a B2B technology marketing or software industry context.

• Experience researching and incorporating innovative AI methodologies into production-level business solutions.

🏝️ Benefits

• Eligibility for bonuses, commissions, and/or equity.

• Flexible work environments, including fully remote options depending on role requirements.

• Reasonable accommodations available for applicants with disabilities.