Machine Learning

Overview

Multiple data science and analytics roles are described across various organizations. The descriptions include responsibilities, qualifications, and posting details for positions such as Data Science Officer, Data Science Associate, Data Science Engineer, Data Science Consultant, Head of Data Science, Data Science Research Executive, AI & Data Science Senior Manager, and related internships. The content is a composite of job postings and contains formatting inconsistencies, mixed HTML tags, and duplicated sections. The refined version below preserves the intent of listing responsibilities and qualifications while organizing content into clear sections with valid HTML tags. This is a cleaned, consolidated representation suitable for publication, without adding new facts.

• Data Science Officer (OnePuhunan / CreditAccess Philippines) – Responsibilities: prototype, test, and deploy ML models; clean and optimize data; collaborate with stakeholders; build dashboards; design AI solutions (NLP, recommendations, predictive analytics); explore generative AI and computer vision; lead experimentation and model monitoring. Qualifications: ≥5 years in data science/ML; SQL, Python, R; strong analytics; degree in Mathematics/Statistics/CS or related; proactive, team-oriented.
• Data Science Associate (Kayana) – Responsibilities: design/develop/deploy ML models; integrate external datasets; strengthen MLOps; prototype with generative AI; mentor interns. Qualifications: proven ML model development experience; Python with ML libraries; ML/Ops knowledge (MLflow, Feast); SQL and cloud (AWS, Databricks); strong communication; ethics in AI; degree in CS/Data Science/Math or related; strong data storytelling and BI tooling (Power BI, Metabase, Superset).
• Data Science Engineer – NLP & LLMs (Remote)
• Data Science Consultant – Responsibilities: define business problems; develop predictive models; present insights; collaborate cross-functionally; posted with salary ranges and hybrid work arrangements. Qualifications: 2+ years DS/ML; Python and data libraries; ML algorithms; Tableau/Power BI; strong analytical and communication skills.
• Head of Data Science – Responsibilities: lead DS initiatives; manage data science team; client engagement; architecture of scalable analytics solutions; project management; 12+ years in DS/analytics; leadership experience; Python/R, SQL; cloud/big data knowledge; banking experience desirable.
• Data Science Research Executive – Responsibilities: join DS team in market research; grow analytics capabilities; learn from experts; growth opportunities. Qualifications: statistics or applied math background; familiarity with market research; knowledge of SAS/SPSS/STATA; English/Filipino; hybrid work; Ortigas Center, Pasig
• AI & Data Science Senior Manager – Responsibilities: lead end-to-end AI/DS projects; client engagement; mentor team; architecture of scalable analytics; business development; requirement gathering; 12+ years in DS/AI; IT consulting background preferred. Skills: Python, R, SQL; cloud, big data, AI/ML; NLP/Computer Vision; Git/Agile; strong presentation & consulting skills.
• Data Science Internships (Aboitiz Foods) – Responsibilities: support data tasks; data prep, cleaning, simple analysis; create reports/visualizations; learn real-world DS practices. Qualifications: currently pursuing Bachelor's in CS/DS/IT/etc.; coursework in data visualization, data structures/algorithms, SQL, ML basics, cloud fundamentals; 360+ work hours; ability to work onsite or hybrid.

• Locations include Pasig City (NCR), Muntinlupa, Taguig, and remote options where stated.
• Salary ranges vary by role and organization; examples include ₱60,000-80,000 gross for Data Science Consultant, and higher ranges for senior/lead roles.
• Posted dates range from today to 1 day ago, with some postings indicating ongoing opportunities.

Content is a compilation of multiple job postings. It contains varied formats, duplicated sections, and some inconsistent phrasing. The refined version organizes core responsibilities and qualifications per role, excludes irrelevant boilerplate, and preserves the original information without introducing new facts.