Snr. Business Data Analyst
- Candidate must possess at least a Bachelor’s/College Degree in Mathematics, Economics, Information, Computer, and Technology or equivalent
- With 5-10 years of working experience in data science, data analytics, or quantitative analysis
- At least 5 years of working experience with data gathering and preparation for ML models
- Understanding of machine-learning algorithms and operations research
- Technical knowledge on data mining and end-to-end process of data modeling
- Proficient in utilizing R/Python and SQL to extract, manipulate, and analyze datasets
- Experience building data infrastructure and implementing reporting solutions
- Experience with Tableau, Power BI, Mode analytics, Looker, or other data visualization tools
- Experience developing and deploying ML solutions in a public cloud such as Azure, AWS, or Google Cloud Platform
- Knowledge of business concepts and processes such as opportunity management, value chain, Logistics, forecasting, marketing programs, pricing, sales/marketing cycle & funnel
- Experience in the agricultural and/or healthcare industry is a preferred
- Experience in retail and/or wholesale business models is a plus
- Excellent written and verbal communication skills as well as presentation skills
- With a track record of proven ability to communicate complex technical topics to technical as well as non-technical people
- Ability to manage multiple projects at once and re-prioritize quickly is a must
- Ability to operate with a high level of professionalism and maturity with less supervision
OTHER KEY CONSIDERATIONS:
- Must be highly organized and able to work in a fast-paced environment
- Must be able & willing to learn new tools, software, and processes
- Must be able to take direction, listen to the needs of business managers, and interpret their needs into technical instructions
- Must be effective working on teams, within, and outside of function
DUTIES AND RESPONSIBILITIES:
- Conduct research and development in cutting-edge areas of Machine Learning, Deep Learning, and Computer Vision, including Object Detection, Object Recognition, Image Document Classification, and many more that can be applied to product development
- Implement state-of-the-art Machine Learning, Deep Learning, and Computer Vision algorithms that run on embedded devices, applications, servers, and cloud
- Assist in the Proof of Concept (POC) and create data solutions.
- Design and prototype solutions in response to critical market needs to be defined by product management and top management
- Extract, transform, and analyze data using statistical techniques that will help the organization make business decisions based on data
- Develop/Create and implement data collection systems, data analytics, and other strategies that optimize statistical efficiency and quality
- Identify, analyze, and interpret trends or patterns in complex data sets
- Filter and “clean” data by reviewing computer reports, printouts, and performance indicators to locate and correct code problems
- Perform data analysis that provides a platform for decision-making on a variety of business issues Apply your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and guide applicable next steps
- Understand the needs and priorities of the organization to create detailed models
- Conduct/Run statistical analyses to extract actionable insights that influence, support, and assist in product decisions and launches
- Present proposals and results in a clear manner backed by data and coupled with actionable conclusions
Develop and maintain ETL processes to ensure data quality, consistency, and accuracy. Transform and clean data as needed for downstream consumption.
Create clear and informative data visualizations and reports to communicate findings to both technical and non-technical stakeholders.
Develop and implement appropriate statistical and machine learning techniques to make predictions, classify data, and solve specific business challenges.
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