Kumar Abhinav

Data Scientist

Bengaluru, Karnataka, India3 yrs 9 mos experience

Key Highlights

Increased patient retention by 25% through predictive modeling.
Saved $200k monthly via optimized drug inventory.
Generated $800k additional revenue with Power BI dashboards.

Stackforce AI infers this person is a Data Scientist with expertise in Healthcare analytics and cloud-based data solutions.

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Skills

Core Skills

Predictive ModelingData EngineeringData VisualizationQuality AssuranceData AnalysisBusiness AnalysisLeadership

Other Skills

Amazon RedshiftAmazon Web Services (AWS)SQLPythonPower BICollibraDBTMentoringBusiness InsightsQualitative ResearchQuantitative ResearchIdentifying TrendsDigital AnalysisHypothesis TestingExternal Communications

About

Analytical Data Scientist with 3.5 years of experience in business intelligence, specializing in insights for Fortune 500 clients. Expert in predictive modeling, data engineering, and cloud technologies. Increased patient retention by 25% and saved $200k monthly through inventory optimization. Proficient in Python, SQL, AWS, and machine learning. Skilled in extracting insights from complex datasets to drive strategic decisions and optimize business processes. Proven ability to lead projects and deliver high-impact solutions in fast-paced environments.

Experience

3 yrs 9 mos

Total Experience

2 yrs 2 mos

Average Tenure

1 yr 7 mos

Current Experience

Nielsen

Data Scientist

Nov 2024 – Present · 1 yr 7 mos · Bengaluru, Karnataka, India

Mathco

2 roles

Associate Analyst

Promoted

Oct 2023 – Nov 2024 · 1 yr 1 mo · Bengaluru, Karnataka, India · On-site

Implemented predictive churn model with 77% accuracy, boosting patient retention by 25%.
Migrated 10+ datasets to AWS cloud, reducing processing time by 30% and enhancing system efficiency.
Created Power BI dashboards generating $800k additional revenue through improved decision-making.
Optimized drug inventory using SQL and Python, yielding $200k monthly savings.
Established automated QC checks with Collibra, cutting monthly costs by $40,000.
Enhanced Redshift queries via DBT cloud, improving data transformation and real-time analytics.
Executed ad-hoc analyses, accelerating market growth of new pharmaceutical products.
Aligned data strategies with business objectives across cross-functional teams.
Mentored junior team members, fostering continuous learning in the data science department.