Senior Business Analyst

1 day ago

Manila, National Capital Region, Philippines beBeeDataScientist Full time $126,000 - $154,000

Unlocking business potential through data is at the core of this role. As a skilled professional, you will be responsible for applying advanced statistical analysis, complex data mining, and artificial intelligence techniques to drive value from data.

Key Responsibilities:
  1. Analyzing large datasets to transform raw data into actionable insights that inform strategic business decisions.
  2. Designing and implementing data-driven solutions with specific focus on advanced analytical methods, data models, and visualizations to optimize business outcomes.
  3. Developing predictive simulations and models to provide descriptive analytics solution recommendations that address key business challenges.
  4. Evaluating trends and problems through complex big data analysis to identify opportunities for growth and improvement.

Requirements:

  1. Six (6) years of experience in applied research, big data analytics, statistics, applied mathematics, data science, computer science, operations research or other closely related quantitative or mathematical discipline.
  2. At least three (3) years of direct experience in machine learning.
  3. Advanced Degree (Masters or PhD) in Statistics, Applied Mathematics, Data Science, Computer Science, Operations Research or other closely related quantitative or mathematical discipline. A PhD degree may be substituted for up to three (3) years of relevant experience.
  4. Demonstrates knowledge of data mining methods, databases, data visualization and machine learning.
  5. Ability to communicate analysis techniques, concepts and products effectively to both technical and non-technical stakeholders.
  6. Ability to develop data-driven solutions, data models, and visualizations that meet business requirements.

Desired Experience and Skills:

  1. Familiarity with distributed database technologies such as Databricks.
  2. Proficiency in PySpark and Python programming languages.
  3. Experience with developing complex SQL queries to extract, transform, and load data efficiently.
  4. Knowledge of analytic techniques such as Anomaly detection, Clustering, and Time-series analysis.
  5. Experience implementing NLP concepts including preprocessing, TF-IDF, Named Entity Recognition, and LLMs.

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