Who we Want :
Collaborative partners. People who build and leverage cross-functional relationships to bring together ideas, information, use cases, and industry analyses to develop best practices.
Detail-oriented process improvers. Critical thinkers who naturally see opportunities to develop and optimize work processes finding ways to simplify, standardize and automate.
Analytical problem solvers. People who go beyond just fixing to identify root causes, evaluate optimal solutions, and recommend comprehensive upgrades to prevent future issues.
Job Description :
At Global Data Analytics team, we’re proud to offer innovative products that meet the needs and wants of our Business. To help us continue to grow our offerings, we’re seeking an experienced data scientist to deliver advanced analytics enabled insights to us at speed and with high quality.
Our ideal team member will have the mathematical and statistical expertise you’d expect, but a natural curiosity and creative mind that’s not so easy to find.
As you mine, interpret, and clean our data, we will rely on you to ask questions, connect the dots, and uncover opportunities that lie hidden within all with the ultimate goal of realizing the data’s full potential.
You will join a team of product managers and will slice and dice data using machine learning models, creating new visions for the future.
You have experience with advanced analytics methods including clustering, classification, sentiment analysis, time series, and deep learning.
What you will do :
Collaborate with the Business to ideate and conceptualize the advanced analytical use cases enabling business to grow and win
Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
Work as the lead data strategist, identifying and integrating new datasets that can be leveraged through our product capabilities and work closely with the engineering team to strategize and execute the development of data products
Execute analytical experiments methodically to help solve various problems and make a true impact across various domains and industries
Identify relevant data sources and sets to mine for client business needs, and collect large structured and unstructured datasets and variables
Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy
Analyze data for trends and patterns, and Interpret data with a clear objective in mind
Implement analytical models into production by collaborating with software developers and machine learning engineers.
Communicate analytic solutions to stakeholders and implement improvements as needed to operational systems
Perform high level estimation and roadmap for the advanced analytical use cases
Work with product managers to assist in product feature prioritization
What you need :
Bachelor's Degree in statistics or applied math or engineering
Master’s Degree in a stats, applied math, or related discipline is preferred
Strong experience in a data science role, minimum 8-10 years of relevant experience required
At least 5 years’ experience in Python, Scala, or R for large scale data analysis
Proficiency with data mining, mathematics, and statistical analysis
Advanced pattern recognition and predictive modeling experience
At least 5 years’ experience with machine learning
At least 5 years’ experience with relational databases
Exceptional writing and editing skills combined with strong presentation and public speaking skills
Physical & mental requirements :
Demonstrated strong communication and influencing skills oral, written, listening, executive presentations
Demonstrated ability to partner with business representatives at all levels to identify needs, define and document requirements, and drive products
Demonstrated ability to guide the business towards optimal products
Demonstrated ability to maintain clear communication channels with IT and business stakeholders
Demonstrated ability to explain complex technical concepts to a non-technical audience