Data Scientist

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

📋 Description

• Engage in comprehensive classification and forecasting projects, covering problem identification, data preparation, model creation, evaluation, and initial deployment support (e.g., demand forecasting, churn prediction).

• Analyze and clean datasets; conduct Exploratory Data Analysis (EDA) to gain insights into data quality and understand dataset characteristics.

• Create features for both tabular and time-series data.

• Train, validate, and optimize standard Machine Learning models (e.g., logistic regression, decision trees, ensemble methods, gradient boosting, classical time-series models, and simple neural networks).

• Assess models using suitable metrics that clearly influence business KPIs.

• Develop clear visualizations and produce concise reports to communicate insights and model outcomes to business stakeholders.

• Work collaboratively with data engineers and AI engineers to implement models into production (including batch scoring, APIs, monitoring, dashboards).

• Maintain documentation of data sources, modeling assumptions, and experimental outcomes in a reproducible format (such as notebooks, reports, and wikis).

• Convert business requirements into technical objectives by establishing success metrics, evaluating data feasibility, and ensuring alignment with stakeholder expectations.

• Involve in pre-sales activities (for senior consultant roles).

⛳️ Requirements

• Proven commercial experience with a variety of classical data science and machine learning models (e.g., decision trees, ensemble models, linear/logistic regression).

• Strong understanding of customer analytics principles or advanced forecasting methodologies. Experience in:

• Hyperparameter optimization

• Model validation frameworks

• Gathering requirements and translating business needs into technical strategies

• Feature engineering and model assessment

• Previous experience in an analytical role supporting business operations (preferred).

• Proficiency in Python and a working knowledge of SQL.

• Familiarity with common data science and machine learning libraries.

• Significant experience with at least one cloud platform: Databricks, GCP, or Azure.

• Basic programming skills and a grasp of fundamental programming concepts.

• Strong business insight.

• Experience with advanced modeling techniques such as deep learning or reinforcement learning (preferred).

• Capability to devise innovative solutions to customer challenges.

• Nice to have:

• Understanding of causal machine learning.

• Experience with big data and distributed computing environments.

• Demonstrated commercial success with forecasting projects.

• Experience in Object-Oriented Programming (OOP) using Python.

• Familiarity with MLOps practices and tools. Knowledge of additional languages such as R or Scala is a plus.

🏝️ Benefits

• Competitive salary package.

• Opportunities for professional development and growth.

• Flexible working hours.

• Collaborative and innovative work environment.