Data Analyst Machine Learning

PROFILE SUMMARY

Experienced Data Analyst with *+ years of expertise in analyzing large datasets within the financial and IT sectors, leveraging Python, SQL, PostgreSQL, and Power BI to drive data-driven decision-making.

Proficient in predictive modeling using machine learning algorithms (Random Forest, Logistic Regression, Scikit-learn) to enhance risk assessment, detect fraudulent transactions, and improve financial forecasting accuracy.

Skilled in ETL workflows and data transformation, utilizing Apache Spark and PostgreSQL to streamline data extraction, processing, and integration, ensuring high data quality and accessibility for financial analysis.

Experienced in developing real-time dashboards with Power BI and automating reporting processes using Alteryx, improving financial reporting efficiency and accelerating decision-making for banking and investment stakeholders.

Experienced Data Analyst with demonstrated expertise in analyzing large and complex datasets in financial and IT sectors.

Adept at translating business challenges into data-driven solutions using Python, SQL, and cloud-based technologies.

Proficient in developing predictive models, real-time dashboards, and ETL pipelines.

Strong foundation in statistical modeling, data visualization, and business intelligence with hands-on knowledge of Tableau, Dynamics 365, and modern Java frameworks.

TECHNICAL SKILLS

Methodologies:

SDLC, Agile, Waterfall

Data Science & Analytics:

Predictive Modeling, Risk Analysis, Data Wrangling, ETL, A/B Testing

Programming Language:

Python, SQL, Java, Scala, R

Packages:

NumPy, Pandas, Matplotlib, SciPy, Scikit-learn, TensorFlow, Seaborn, ggplot2

Visualization Tools:

Tableau, Power BI, Advanced Excel (Pivot Tables, VLOOKUP)

IDEs:

Visual Studio Code, PyCharm, Jupyter Notebook, IntelliJ

Cloud Technologies:

AWS (EC2, S3, Redshift, Athena, Glue, DynamoDB), Azure, Snowflake

Database:

MySQL, PostgreSQL, MySQL, MongoDB, SQL Server

CRM & ERP:

Microsoft Dynamics 365 (Dashboards, Reporting, Integration)

Other Technical Skills:

Machine Learning Algorithms, ETL Tools, Statistics, ServiceNow, SSIS, SSRS, MapReduce, Snowflake, Alteryx, Probability distributions, Confidence Intervals, ANOVA, Hypothesis Testing, Regression Analysis, Linear Algebra, Advance Analytics, Data Mining, Data Visualization, Data warehousing, Data transformation, Data Storytelling, Business Analysis, Association rules, Clustering, Classification, Regression, A/B Testing, Forecasting & Modelling, Data Cleaning, Data

Wrangling, Informatica MDM, Jira, FRD BRD, Gap Analysis, Cost Benefit Analysis, Risk Analysis, UAT, JAD, Supply Chain Management

Libraries & Frameworks:

Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, Seaborn, Spring Boot, Hibernate

Version Control Tools:

Git, GitHub

Business Skills:

Stakeholder Engagement, Requirement Analysis, Report Automation, Agile & Scrum

Operating Systems:

Windows, Linux, Mac iOS

WORK EXPERIENCE

Wells Fargo, Canada Aug 2023 – Present Data Analyst

Designed and implemented end-to-end data pipelines using Apache Spark and PostgreSQL to process credit portfolio datasets, ensuring efficient data extraction, transformation, and loading (ETL).

Developed robust ETL frameworks for handling large-scale transactional data, supporting data quality, lineage, and monitoring across financial data systems.

Optimized data warehousing infrastructure on AWS using Redshift, Athena, and S3 for scalable querying, storage, and performance enhancement of 50M+ financial records.

Integrated Microsoft Dynamics 365 with internal data platforms to automate CRM data flow, improving operational transparency and streamlining financial reporting.

Built and deployed real-time reporting dashboards using Tableau and Power BI, empowering credit analysts to monitor key financial indicators and portfolio risk.

Engineered scalable data models to support credit risk evaluation systems, working closely with data science teams to provision high-quality datasets for machine learning models.

Applied Matplotlib and Seaborn to generate executive-level visual narratives for stakeholder engagement, highlighting borrower segmentation and credit trends.

Collaborated with cross-functional financial teams to align reporting workflows with regulatory compliance and audit requirements.

Enhanced data retrieval speed and accuracy through query tuning and optimization, improving time-to-insight for risk analysis and loan evaluation workflows.

Accenture, India Jul 2020 – Jul 2022

Data Analyst

Designed and deployed predictive analytics models for financial forecasting using Python libraries including Pandas, NumPy, and SciPy, supporting accurate business planning and investment strategies.

Built interactive Tableau dashboards that provided comprehensive visibility into key performance indicators (KPIs), streamlining decision-making processes for investment and operations teams.

Integrated Microsoft Dynamics 365 with reporting systems to centralize client data, automate financial tracking, and enhance customer relationship management insights.

Wrote and optimized complex SQL queries for efficient data extraction, transformation, and validation across legacy and modern financial data systems.

Conducted extensive model validation, data cleaning, and preprocessing to ensure consistency, accuracy, and readiness of datasets for advanced analytics and reporting.

Partnered with business and technical teams to embed analytical insights into enterprise-wide dashboards and reporting tools, improving stakeholder engagement and data accessibility.

Leveraged SAP’s integrated modules to manage financial data, enabling real-time insights and improving the efficiency of operational workflows.

Improved forecasting and scenario modeling by applying advanced statistical techniques with Python, enhancing the accuracy of financial trend analysis and strategic projections.

Implemented Apache Kafka to support real-time data streaming and processing pipelines, significantly improving the timeliness of analytics and reporting across teams.

Used Jira for agile task management, tracking progress and ensuring timely delivery of data analytics projects across cross-functional teams.

EDUCATION

Master’s in electrical & computer engineering (2022-2024)

Carleton University, Ottawa, Canada

Bachelors in Electronics & Communications Engineering (2018- 2022)

JSS Academy of Technical Education, Bengaluru, Karnataka, India.

Simran Jitendra Navani

DATA ANALYST

Ottawa, Canada } 732-***-**** } ***************@*****.***}

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