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Data Scientist - Analytics
Simarn Solutions
- Irving, Texas, United States
- Irving, Texas, United States
About
Responsibilities
Conducted data analysis and exploratory analysis using Python and SQL to support business and product reporting needs.
Supported machine learning initiatives by preparing clean, structured datasets from raw operational data.
Assisted in developing and maintaining data pipelines to extract, transform, and load data into Snowflake.
Performed data cleaning, validation, and consistency checks to ensure accuracy and reliability of analytics outputs.
Analyzed transactional, order, and log data to identify trends, usage patterns, and system behavior.
Supported the definition and tracking of KPIs and performance metrics used by product and engineering teams.
Developed and maintained Power BI and Tableau dashboards for recurring business reviews and reporting.
Assisted with feature preparation and basic feature engineering for predictive modeling efforts.
Built and supported ETL/ELT data pipelines to ingest and transform operational data into Snowflake.
Implemented data validation and quality checks within pipelines to ensure reliable downstream analytics.
Automated recurring data extraction and transformation workflows using Python and SQL.
Collaborated with engineering teams to understand data sources and resolve data-related issues.
Helped identify data gaps and anomalies during analysis and reporting activities.
Contributed to documentation for datasets, queries, and reporting logic to support team knowledge sharing.
Participated in cross-functional discussions to translate business questions into data and analytics tasks.
Supported ad-hoc data analysis requests from stakeholders as needed.
Skills Analytics & Data Science: Exploratory Data Analysis (EDA), Statistical Analysis, Feature Engineering, Predictive Modeling, Forecasting, Classification, Clustering, Anomaly Detection, Root Cause Analysis, KPI Definition & Tracking, Data Quality Validation, Business Insights, Documentation & Reporting
Machine Learning & AI: Supervised & Unsupervised Learning, Regression, Classification, Time Series Models (ARIMA, SARIMA, Holt-Winters), Deep Learning, Generative AI, Model Evaluation, Hyperparameter Tuning, MLflow
NLP & Generative AI: GPT-4, Gemini, LLaMA, BERT, LangChain, RAG Pipelines, Hugging Face Transformers, FAISS, Sentiment Analysis, Semantic Search, Prompt Engineering
Visualization & BI: Power BI, Tableau, Streamlit, Dash
Methodologies & Concepts: SDLC, Agile (Scrum), Data Lifecycle, Experimentation, A/B Testing, Business Requirement Analysis
Certifications
AWS Cloud Practitioner: Certified in foundational AWS cloud concepts including core services, security, pricing, and cloud architecture.
Databricks with Generative AI: Certified in applying Databricks capabilities for generative AI use cases, including model training, deployment, and data pipeline integration.
Databricks Fundamentals: Certified in Databricks core functionalities, covering data management, collaborative workflows, and analytics.
Generative AI Fundamentals: Certified with knowledge of core generative AI concepts, applications, and responsible AI practices.
GenAI Tools & AI Agents for Software Testing: Certified in applying GenAI tools and AI-driven agents to enhance efficiency and coverage in software testing processes.
Generative AI Application Development: Certified in developing, integrating, and deploying applications using generative AI frameworks and tools.
Education University of North Texas – Denton, Texas
Master’s in Data Analytics – Dec 2024
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Languages
- English
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