DATA MANAGEMENT AND ANALYTICS SPECIALIST (AI AND MACHINE LEARNING)

  • Taguig City, Metro Manila
  • Permanent
  • Full-time
  • 1 month ago
Make your next big career move by applying as KMC Solutions' next DATA MANAGEMENT AND ANALYTICS SPECIALIST! We are seeking a highly motivated and skilled Contingent Worker to join our team as a Data Management and Analytics Specialist. This role will be pivotal in transforming raw data into actionable insights and developing intelligent AI/ML solutions to solve complex business challenges. The ideal candidate will possess a strong analytical mindset, proficiency in data manipulation and statistical modeling, and a solid understanding of machine learning principles and applications. You will work closely with cross-functional teams to drive data-driven decision-making and innovation across various projects. You will play a crucial role in transforming raw data into actionable insights, building and deploying AI models, and improving the accessibility and utility of our organizational knowledge. This position offers exposure to diverse datasets and complex challenges within a collaborative environment. The main responsibilities of a DATA MANAGEMENT AND ANALYTICS SPECIALIST include: Data Analysis & Modeling: Collect, clean, and preprocess large, complex datasets from various sources. Perform exploratory data analysis to identify trends, patterns, and anomalies. Translate concepts into data flows, processes and key outputs that enable intuitive user experiences and promote data relevance. Translate complex analytical findings into clear, actionable insights for non-technical stakeholders. Create compelling dashboards and visualizations to communicate insights effectively using tools like Tableau, Power BI, or similar. Prepare and present findings to internal stakeholders, including leadership and cross-functional teams. Knowledge Management (KM) Enhancement: Proficient in Knowledge Management platforms (wiki's, intranets, handbooks, etc) and possess the ability to learn and engage with new platforms quickly Potentially leverage AI techniques (e.g., semantic search, knowledge graphs) to enhance knowledge discovery and retrieval. Contribute to the creation and maintenance of a centralized knowledge repository. Artificial Intelligence (AI) Development: Explore and experiment with new AI/ML technologies and frameworks to improve existing systems or create new capabilities. Work and collaborate with business technology and engineering teams to integrate AI models into production systems. Collaboration: Work closely with business users, domain experts, IT teams, and other data professionals to understand requirements and deliver impactful solutions. Participate in brainstorming sessions and contribute to the overall data strategy. To apply, you must be an expert on the following requirements: Willing to work onsite (SM Aura) and night shift (EST). Bachelor's degree with 2+ years of proven experience in a Data Analytics role,Knowledge Management or similar role. Strong proficiency in ServiceNow or any case management tool for data analysis and model development. Experience with data extraction and manipulation. Familiarity with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn). Demonstrated experience with Knowledge Management principles and systems, including information architecture, content classification, and search optimization. Excellent analytical, problem-solving, and critical thinking skills. Strong communication and presentation abilities, with the capacity to explain complex technical concepts to non-technical audiences. Ability to work independently and as part of a team in a fast-paced environment. It will also be favorable if you are knowledgeable in: Experience with systems or platforms for data storage, processing, and machine learning services. Familiarity with big data technologies (e.g., Spark, Hadoop). Knowledge of graph databases or knowledge graph technologies. Previous experience working as a contingent worker or on project-based engagements. Show more Show less

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