 data science talent data science talent hemraj mon 10272025 828 data science talent want to show in why divihn homepage talent mobilization solutions talent mobilization image healthcare industries healthcare image manufacturing industries manufacturing image why divihn homepage image our customer is a healthcare services organization that develops and delivers pointofcare technology to improve care coordination compliance and physicianpatient interactions founded in 2006 the organization has doubled each year in its scale of technology implementation at outpatient healthcare facilities business partnerships with global life sciences and medical device companies product innovation and team growth the organization s pointofcare technology platform impacts 500m patient visits annually the challenge the customer organization employed a proof of play auditing process in order to show stakeholders that relevant content was displayed on digital displays of more than 100000 devices that has been installed in doctor s offices all over the country the proof of play process leveraged the technology of image processing and exif data the customer s data engineering and data science team was tasked with helping passage this proofofplay batch process to run in real time the team quickly decided on the tech stacks of aws microservices lambda s3 and rds with python as the programming language their challenge however was one of staffing the data science engineering team had to necessarily scale quickly in order to support the rapidly growing installbase and finding the right talent proved to be a challenge in light of the customer s allocated budget and the short supply of experienced professionals in this highdemand area our solution in order to address the customer s challenge divihn designed and implemented an alternative talent solutions program that involved augmenting the customer s existing data science engineering team with a data science pod composed of young data scientists with a master s degree in data analytics and 23 years of related experience the starting point involved an intake call with project stakeholders at the client which included the customer s vice president for growth solutions the director of the data engineering team and the head of the human resources team to get a deeper understanding of the organization s requirements challenges culture budget and then jointly map out a staffing strategy and execution plan the plan included a sourcing strategy assessment process and onboarding timelines the candidates we identified for this engagement were largely sourced through our referral network identified candidates were put through an online data analytics test that involved livecoding a skypebased technical interview with our inhouse assessor and a behavioral skills interview with our clientrelationship manager before being presented to the customer since the bulk of the candidate assessments were completed by divihn the customer did not have to spend much time on interviewing candidates thus allowing them time to focus on their core business the team that divihn formed for the customer were assigned onsite mentors and a brief onthejob training program to help them become productive quickly in addition divihn s clientrelationship manager continued to stay in close touch with the deployed resources in addition to periodic cadences with the project stakeholders to collect feedback on performance and progress highlights in view of the customer s urgency to scale the team as quickly as possible to mitigate serious business impacts divihn presented the first slate of techscreened candidates to the customer within 72 hours of the initial intake call following a final interview by the client project manager divihn speedtracked the background check process and onboarding to enable the team to be onsite within just 3 weeks of the customer s reach out to us talent mobilization solutions talent mobilization image healthcare industries healthcare image manufacturing industries manufacturing image  