About me

Hey there! I'm Mohit Jain, the data wizard who transforms raw data into powerful insights and compelling stories. With a passion for unraveling complex data puzzles, I've spent the last 5 years weaving my magic through the realms of Product, Customer Experience, Insurance, Academia, and Finance.

My journey in the world of data has taken me through the corridors of tech giants like Microsoft and Amazon, where I've leveraged my expertise to uncover hidden patterns, optimize processes, and drive data-informed decisions. My data sorcery has:

  1. Improved operational efficiency of a web application at Microsoft and development of new features
  2. Automated technical analyses at Amazon that would take 3 analysts 2 weeks to complete, now down to mere 9 minutes
  3. Optimized queries by 25% for a Insurance Client

But wait, there's more! As a triple-threat data virtuoso, I seamlessly blend the roles of analyst, engineer, and scientist:

  1. Data Analytics: I craft spellbinding Power BI and Tableau dashboards and reports that turn raw data into visual masterpieces, enabling stakeholders to grasp complex trends at a glance. My expertise in SQL, Python, and R allows me to extract insights from the most stubborn datasets.
  2. Data Engineering: I architect robust ETL pipelines and data models that form the backbone of data-driven organizations. From optimizing SQL Server performance to orchestrating data flows with SSIS and Azure Data Factory, I ensure your data infrastructure is built for speed and scale.
  3. Data Science + ML : Armed with machine learning algorithms and statistical techniques, I predict future trends and uncover hidden patterns in your data. Whether it's developing predictive models with scikit-learn or conducting A/B tests to optimize user experiences, I bring scientific rigor to data-driven decision making.

So, whether you need someone to wrangle unruly datasets, craft killer dashboards, optimize data-pipelines, I'm your go-to guy. Let's turn your data dilemmas into data triumphs! Let's connect and turn your data into your most valuable asset.

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Daniel lewis

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Resume IN

Experience

  1. Microsoft

    Redmond, WA

    Business Intelligence Analyst (Contract)

    Apr 2023 — Sep 2024

    Working on product analytics of a customer/tenant management application - M365 Lighthouse that supports Small and Medium Businesses (SMB) with securing and managing their user, data, and devices

  2. Amazon

    Seattle, WA

    Business Analyst (Contract)

    Sep 2022 — Apr 2023

    Developed a dynamic KPI Dashboard monitoring NPS and CSAT, automated multiple business analyses, and conducted end-to-end report Quality Assurance (QA)

  3. Fiverr

    Seattle, WA

    Data Analyst

    Apr 2023 — Present

    Developed and optimized SSRS reports, ETL pipelines, and database queries to enhance Provider Network Operations (PNO) for a health insurance client

  4. University of Washington

    Seattle, WA

    Research Assistant

    Apr 2023 — Present

    Co-authored a research paper on machine learning architecture for NLP applications under the guidance of Prof. Cecilia Aragon, optimizing a model to process 176 million data points with 83% accuracy, and developed data visualizations featured in the publication

  5. ARS Associates

    Kolkata, India

    Data Analyst

    Apr 2023 — Present

    Led multifaceted data-driven initiatives, from crafting Power BI reports for market insights to automating analysis with Python while optimizing SQL queries for efficient data retrieval across diverse business units

Education

  1. University of Washington

    Seattle, WA

    Bachelor's in Human Centered Design Engineering and Data Science

    Sep 2018 — Jun 2022

    GPA: 3.75/4.0; Minor in Mathematics

Certifications

  1. Microsoft Certified: Power BI Data Analyst Associate (PL-300)

    Jan 2024

  2. Udemy: The Advanced SQL Server Masterclass For Data Analysis

    Jun 2023

Skills

  1. BI Tools:

    Power BI (DAX, M, Power Query, Data Modeling), Tableau, MS Excel (Pivot tables, Lookups, Macros), SSRS

  2. Programming Languages:

    Python (Pandas, NumPy, scikit-learn, TensorFlow, SciPy, Matplotlib), SQL (Windows functions, Stored Procedures, Views, User Defined Functions, Indexes, Joins), KQL, R, Java, VBA

  3. Big Data Tools:

    PySpark, Apache Hadoop, Hive, Kafka, Spark, Airflow, Snowflake, Azure Databricks, SQL Server, MongoDB, SSIS, Azure Data Factory

  4. Statistical Techniques:

    Regression, Predictive Modelling, Hypothesis Testing, Multivariate Testing, Machine Learning

  5. Others:

    Git, Jupyter Notebooks, Docker, Linux, MS Office, Jira, Asana, Workfront, Visio, MS Power Point, AWS, Azure