Data Scientist

LatentView Analytics is a leading global analytics and decision sciences provider, delivering solutions that help companies drive digital transformation and use data to gain a competitive advantage. With analytics solutions that provide a 360-degree view of the digital consumer, fuel machine learning capabilities and support artificial intelligence initiatives., LatentView Analytics enables leading global brands to predict new revenue streams, anticipate product trends and popularity, improve customer retention rates, optimize investment decisions, and turn unstructured data into valuable business assets.

Job Description: Data Scientist

Experience: 5 to 15 Years

Location: Atlanta, Georgia , United States (Remote)

Working hours in CST

Qualifications:

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.
• 3+ years of applied experience in data science, preferably in B2B environments.
• Strong understanding of supervised and unsupervised learning methods, overfitting/underfitting, model validation strategies, and key evaluation metrics such as ROC/AUC, precision, recall, and cross-validation.
• Demonstrated experience building churn prediction or similar customer segmentation models with measurable business impact.
• Expertise in Python or R, with hands-on experience using libraries/frameworks like scikit-learn, TensorFlow/Keras (a plus), pandas, and NumPy.
• Advanced SQL skills for efficient data querying, manipulation, and transformation.
• Familiarity with version control systems such as Git and collaborative development workflows.
• Proven ability to present technical findings in a clear, concise, and compelling manner to stakeholders at multiple organizational levels.
• Excellent problem-solving skills with the ability to navigate ambiguity, identify key issues, and prioritize tasks effectively.

Responsibilities:

• Design, build, and deploy churn prediction models specifically for B2B customer lifecycles, using classification algorithms and advanced feature engineering techniques.
• Perform model performance improvement activities, including hyperparameter tuning, feature selection, and retraining strategies, to maximize predictive accuracy and stability over time.
• Develop clear, data-backed justifications for modeling choices; present the rationale behind algorithms, selected features, and evaluation metrics to both technical stakeholders (e.g., data engineering teams) and business leaders (e.g., sales, marketing, customer success).
• Create compelling presentations, reports, and dashboards that explain model outcomes and recommended business actions in a way that is understandable and persuasive to non-technical stakeholders.
• Establish monitoring processes to detect performance degradation or data drift in production churn models; proactively recommend updates to maintain effectiveness.
• Apply general data science techniques, including supervised and unsupervised learning (regression, clustering), data preprocessing, and advanced analytics to broader business problems beyond churn.
• Partner with CRM, product, and data engineering teams to embed churn scores and insights into customer management processes and retention strategies.

At LatentView Analytics, we value a diverse, inclusive workforce and provide equal employment opportunities for all applicants and employees. All qualified applicants for employment will be considered without regard to an individual's race, color, sex, gender identity, gender expression, religion, age, national origin or ancestry, citizenship, physical or mental disability, medical condition, family care status, marital status, domestic partner status, sexual orientation, genetic information, military or veteran status, or any other basis protected by federal, state or local laws.