Data Scientist - Assistant Manager (Hybrid)
Mandaluyong, National Capital Region
Posted 10 days ago
- Company:
- Gratitude Philippines
- Company Description:
- We At Gratitude Philippines Are Able To Successfully Cater To The Recruitment And Staffing Requirements Of BPO Sector From Onshore To Offshore Locations.We Take Special Care Of Bpo Briefing Process To Gain Maximum Output From The Candidate And Everything The Company Has To Offer. Executive Search Gratitude Philippines Recruitment Services That Help Clients Reduce Cost And Time Associated With Hiring The Right Talent. We Understand That Human Resource Is The Pivotal Element In Success Of Any Business, Thus Our Focus Is On Finding Right Candidates Who Can Contribute To Our Client’s Success. Payroll Management & Staffing Our Comprehensively Vetted Recruitment Process Over 14 Years In The Industry Has Equipped Us To Recruit The Right Candidates For Your Company.Our Pan Philippines Presence And Contract Staffing Facilities Give Unparalleled Access To A Vast Base Of Candidates, Who We Rigorously Screen And Evaluate To Ensure The Right Fit Within Your Organization.
- Contract Type:
- Full Time
- Experience Required:
- 5 to 10 years
- Education Level:
- Bachelor’s Degree
- Gender:
- Any
- Number of vacancies:
- 1
Job Description
• Data Scientist (expert on data modeling and predictive analytics) and not Data Analyst or Data Visualization Specialist
• Knowledgeable on use of Python for use in Machine Learning and Data Modeling – Predictive Modeling, a Must background
• With a background in automation
Responsibilities:
Quantitative Modeling
a. Apply data analysis, data mining and data processing to present data clearly
b. Apply data mining techniques and develop software to investigate leads, identify patterns and regularities in data
c. Develop data models based on advanced statistical modelling, data mining, and machine learning methods
Business Problem Framing: Manage the problem definition and hypothesis formulation process
Analytics Problem Framing
a. Assist in the conceptualization of analytical projects
b. Break down problems to recompose them in ways that are solvable
c. Partner with stakeholders to translate business problems into data science projects
d. Plan the development of analytical solutions from initial design through implementation, prototyping and testing
e. Provide advice on the development of data analysis models based on project requirements
f. Provide subject matter expertise to stakeholders, and maintain an advanced knowledge of trends affecting the industry
Insights Generation
a. Assist with the development of actionable recommendations
b. Evaluate experiment outcomes to draw actionable conclusions
c. Guide stakeholders on how to act on findings
d. Synthesize findings into actionable insights
e. Develop compelling, logically structured presentations including storytelling of research and/or analytics findings
Project Management
a. Assist in planning project timelines and resources needed, and setting work quality guidelines
b. Deliver projects in line with agreed standards, providing fit-for-purpose solutions within time, quality, and budget constraints
c. Prepare documentation to outline data sources, models and algorithms used and developed
Information Systems Implementation
a. Develop prototypes and proof of concepts for the selected solutions
b. Assist with developing new data-discovery tools
c. Implement automated processes to produce quantitative models at scale
d. Work with the development team to build tools to accelerate and automate searching, data visualization, and advanced analytics
e. Determine interface design based on user’s requirements
Data Collection
a. Recommend types of data, and internal and external data sources needed to measure and/or predict outcomes
b. Integrate multiple data sets to build large and complex data sets
Data Processing: Build data flow channels and processing systems to extract, transform, load and integrate data from various sources