Hi, I'm Alifiando Destara Yusuf, a dynamic and results-driven Data Scientist with nearly 4 years of experience in leveraging data to drive business growth and efficiency. My expertise spans Python, ETL processes, predictive modeling, and automation. I have a proven track record of owning and optimizing key processes, including developing impactful Python-based solutions and enhancing business strategies through data-driven insights.

I’m currently available for job opportunities.

About me

Biography

I’m Desta, a passionate Data Scientist with nearly 4 years of experience in the insurance and banking sectors. My journey began with a Bachelor's degree in Informatics Engineering from Telkom University, where I developed a strong foundation in data management and analytical techniques. I further honed my skills by pursuing a Master's in Data Sciences and Business Analytics at ESSEC Business School in Paris. During my time at AXA Mandiri Financial Services, I owned and optimized the telemarketing leads generation model, significantly increasing the company’s APE by over 100%. Currently, I'm expanding my expertise through an internship at BNI, where I independently developed multiple Python-based automations that have drastically improved operational efficiency.

Mission Statement

My mission is to harness the power of data to drive business growth and innovation. I am dedicated to solving complex problems through data analysis, automation, and predictive modeling, enabling organizations to make data-driven decisions that have a real impact.

Current Endeavor

While pursuing my Master's at ESSEC Business School, I have temporarily taken a leave of absence to address personal matters. During this period, I am actively seeking new job opportunities to further sharpen my skills, gain valuable experience, and make meaningful contributions to the industry. Having experienced a slightly different role at BNI, I am confident that my diverse skill set allows me to provide even greater value, making me a more versatile and impactful professional.

Personal Interests

Beyond the professional realm, I’m an avid video gamer with a passion for modding casual games on PC. I enjoy staying on top of the latest tech trends and have built a custom PC that reflects my love for technology—it's become my own version of the Theseus' Ship, as I've gradually upgraded and replaced every component over time, illustrating the idea that "the whole remains the same, even as its parts change." I also play on PS5, enjoying the best of both worlds since I can play Xbox exclusives on my PC. My interests also include following advancements in artificial intelligence and exploring new ways to apply data science in everyday life.

Experience

  • As a Business Analyst Support Intern at BNI, I was entrusted with responsibilities that allowed me to make a significant impact within a short span of time. My role involved closely collaborating with a Business Analyst mentor to gain a deep understanding of business processes, while independently driving key automation and analysis initiatives.

    • Business Process Insights and Collaboration:

      • Mentorship and Learning: Working closely with a seasoned Business Analyst mentor, I gained profound insights into the intricacies of business processes and the strategic decision-making involved in a large financial institution like BNI. This mentorship equipped me with the knowledge and skills necessary to contribute effectively to the team.

    • Python-Based Automations:

      • Routine Data Entry Automation: Recognizing inefficiencies in a repetitive data entry task, I independently developed a Python-based automation that reduced processing time from several days to just a few clicks. This automation not only saved significant time but also minimized the risk of human error, thereby improving overall accuracy.

      • Process-Specific Automation: I streamlined a complex process involving different data sets by developing another Python-based automation. This solution resulted in substantial time savings and enhanced the accuracy of outputs, demonstrating the power of automation in handling intricate data processes.

      • Pendataan SLIK Automation: One of my most impactful contributions was the creation of a Python notebook to automate the previously tedious and time-consuming task of "pendataan SLIK." This automation transformed the process into a single, efficient run and was highly praised by the department head for its effectiveness and quality. The recognition underscored the value of my work and its positive impact on the department.

    • Financial Analysis and Reporting:

      • In-Depth Company Analysis: I conducted thorough financial analysis of 8 companies, using their financial reports and directly acquiring necessary data to evaluate their creditworthiness. This analysis played a crucial role in informed decision-making regarding credit approval.

      • Structured Reporting: I produced comprehensive reports following a structured template, ensuring consistency and clarity across all evaluations. These reports were instrumental in providing clear, actionable insights to stakeholders.

  • During my tenure as a Data Scientist at AXA Mandiri Financial Services, I played a pivotal role in enhancing the company’s data-driven decision-making processes. I was responsible for owning and optimizing key models and strategies, particularly in the realm of telemarketing, customer segmentation, and data quality control.

    • Telemarketing Leads Generation Model:

      • Ownership and Optimization: I owned and continuously optimized the telemarketing leads generation model, which utilized both AXA’s and Bank Mandiri's data. This model was instrumental in predicting the optimal times for Telemarketing Sales Officers (TSOs) to contact potential customers, leading to an increase in Annual Premium Equivalent (APE) by over 100%.

      • Data Integration: My deep familiarity with both AXA’s and Bank Mandiri's datasets allowed me to seamlessly integrate and analyze information from these sources, ensuring that the model was as accurate and effective as possible.

      • Predictive Modeling with XGBoost: I developed a highly accurate predictive model using XGBoost, which was trained to predict the top 10 customers each TSO should call during specific hours, based on the likelihood of a successful outcome.

    • Customer Segmentation:

      • Targeted Marketing Strategies: I led customer segmentation initiatives using Bank Mandiri's data, developing highly targeted marketing strategies that significantly improved the focus and effectiveness of campaigns. By identifying key trends and patterns in customer behaviors, I was able to inform more personalized and effective marketing efforts.

      • Advanced Statistical Techniques: I applied a range of advanced statistical techniques, including loss functions and variance explanation methods, to compare and optimize performance metrics. These analyses not only improved the precision of our models but also provided deeper insights into customer behavior.

      • Implementation of PyDQC: To maintain high standards of data quality, I implemented PyDQC (Python Data Quality Control) for monthly bank data. This tool allowed for automated checks on data integrity and consistency, ensuring that the data used in our models and analyses was of the highest quality.

    • Data Visualization and Stakeholder Communication:

      • Visualizations for Decision-Making: I developed polished visualizations that effectively communicated the results of my data analyses to stakeholders, facilitating data-driven decision-making at various levels of the organization. These visualizations were tailored to meet the specific needs of different audiences, from technical teams to senior management.

      • Stakeholder Collaboration: Throughout my role, I collaborated closely with various stakeholders, ensuring that the data insights were aligned with business objectives and contributed to the overall strategic goals of the company.

  • During my internship at Handmadenesia, I developed a strong foundation in data analysis and web development, demonstrating a passion for learning and a commitment to continuous improvement.

    • Analytical Problem-Solving:

      • Effective Solutions Development: Leveraging my analytical and problem-solving skills, I developed innovative solutions for challenging situations, ensuring the successful resolution of technical and operational issues.

      • Data Visualization with Kibana: I utilized Kibana to analyze and visualize data, creating interactive dashboards that provided actionable insights for decision-making. My work with Kibana allowed the team to monitor and assess key metrics in real-time, enhancing overall data-driven strategies.

    • Web Development and Technical Skills:

      • Web Development: I contributed to the development and enhancement of web applications, applying my technical skills to create user-friendly and efficient solutions.

      • Adaptability and Learning: Demonstrating adaptability, I quickly and efficiently learned new concepts and tools, applying them to projects with proficiency and confidence.

    • Team Collaboration and Relationship Building:

      • Effective Communication: I developed and maintained courteous and effective working relationships with team members and stakeholders, fostering a collaborative and productive work environment.

      • Continuous Improvement: My commitment to continual improvement was evident in my proactive approach to learning and applying new skills, contributing to the success of the projects I was involved in.

  • As a Software Tester and Content Creator Intern at Bazaar Entertainment, I played a critical role in ensuring the quality and creativity of our software products in a fast-paced environment.

    • Quality Assurance and Testing:

      • Manual Exploratory Testing: I conducted thorough manual exploratory testing of software applications, identifying and addressing potential issues to ensure a smooth user experience.

      • Attention to Detail: My keen attention to detail allowed me to meticulously test and validate software functionality, contributing to the overall reliability and performance of the products.

    • Creative Content Development:

      • Visual Novel Creation: Using TyranoBuilder Visual Novel Studio, I created engaging visual novel content, combining storytelling with interactive design to enhance user engagement.

    • Team Collaboration and Self-Motivation:

      • Teamwork and Support: I worked effectively in a team setting, providing support and guidance to colleagues while also taking on significant individual responsibilities.

      • Self-Motivation: Demonstrating a strong sense of personal responsibility, I consistently delivered high-quality work, meeting deadlines and exceeding expectations.

Notable Projects

    • Description: Created a Python-based automation for BNI that transformed the previously tedious and time-consuming task of "Pendataan SLIK" into a single, efficient process. The automation compiled data from multiple SLIK PDF files and generated a ready-to-use Excel file, with each sheet containing data for different entities.

    • Role: Sole developer, responsible for designing and implementing the automation.

    • Technologies Used: Python, PyPDF2, Pandas, OpenPyXL.

    • Challenges: Extracting and processing unstructured data from complex PDF files, ensuring data integrity, and handling large volumes of files in bulk.

    • Solutions: Developed a robust Python script that automated the extraction, processing, and compilation of data from SLIK PDFs. The automation could handle bulk processing, significantly reducing manual effort and improving accuracy.

    • Impact/Results: The automation drastically reduced processing time, minimized human error, and was highly praised by the department head for its effectiveness.

    • Description: Developed and optimized a telemarketing leads generation model for AXA Mandiri Financial Services. This model predicted and assigned the top 10 customers each Telemarketing Sales Officer (TSO) should call during each working hour to maximize efficiency.

    • Role: Owner and developer of the model, responsible for data integration, feature engineering, and model deployment.

    • Technologies Used: Python, XGBoost, Pandas, NumPy, PyDQC.

    • Challenges: Integrating and analyzing vast datasets from both AXA and Bank Mandiri, ensuring data quality and consistency, and achieving high model accuracy.

    • Solutions: Implemented advanced feature engineering and used PyDQC for data quality control. Developed a highly accurate predictive model using XGBoost, which led to a more than 100% increase in Annual Premium Equivalent (APE).

    • Impact/Results: The model optimized telemarketing efforts, significantly increasing conversion rates and overall business performance.

  • Description:
    At AXA Mandiri Financial Services, I developed a sophisticated Customer Segmentation Dashboard designed to provide actionable insights into customer behaviors and preferences. The dashboard was integral to helping the marketing and sales teams tailor their strategies by identifying distinct customer segments based on their interactions, demographics, and purchasing patterns.

    Role:
    I led the end-to-end development of the dashboard, handling everything from data extraction and segmentation analysis to visualization and deployment.

    Technologies Used:

    • Python: For data processing, segmentation analysis, and creating visualizations.

    • Pandas and NumPy: Utilized for data manipulation, feature engineering, and identifying customer segments.

    • Scikit-learn: Applied for implementing clustering algorithms to define customer segments.

    • Matplotlib and Seaborn: Used for creating visualizations that were integrated into the dashboard.

    • SQL: Employed for querying and managing the underlying customer data.

    • PyDQC: Used to ensure data quality and consistency before segmentation analysis.

    Challenges:

    • Data Integration: Customer data was sourced from multiple platforms, including AXA and Bank Mandiri, each with unique formats and structures. Integrating these datasets into a unified format was a critical challenge.

    • Segmentation Accuracy: Accurately identifying customer segments that were meaningful and actionable required careful feature selection and engineering.

    • User-Friendly Visualization: Ensuring the dashboard was intuitive and user-friendly for non-technical users, such as marketing and sales teams, was essential for its adoption and effectiveness.

    Solutions:

    • Data Aggregation and Cleansing: I aggregated and cleansed customer data from various sources, ensuring consistency and reliability across the datasets. PyDQC was utilized to automate the data quality control process, ensuring that only clean, consistent data was used for segmentation analysis.

    • Advanced Segmentation Techniques: Using Scikit-learn, I implemented clustering algorithms, such as K-Means and Hierarchical Clustering, to identify distinct customer segments. These segments were refined through iterative analysis and validated with feedback from stakeholders.

    • Dashboard Development: I developed the Customer Segmentation Dashboard using Python, Matplotlib, and Seaborn for visualizations. The dashboard featured intuitive graphs, charts, and filters that allowed users to explore different customer segments in depth, understand their characteristics, and make data-driven decisions.

    Impact/Results:

    • Enhanced Marketing Strategies: The Customer Segmentation Dashboard provided clear, actionable insights into various customer groups, enabling the marketing and sales teams to design more targeted and effective campaigns.

    • Increased Customer Engagement: By addressing the specific needs of different segments, the company saw improved customer engagement and satisfaction.

    • Data-Driven Decision Making: The dashboard became a central tool for making informed decisions, helping the company allocate resources efficiently and optimize business performance.

    • Description: For my Bachelor's thesis at Telkom University, I developed a classification model to accurately identify snakebite images using the Random Forest algorithm. This project contributed to medical research by providing an efficient method for classifying snakebite images.

    • Role: Researcher and developer, responsible for data collection, model development, and evaluation.

    • Technologies Used: Python, Random Forest, OpenCV, Scikit-learn, Matplotlib.

    • Challenges: Handling a diverse set of images, extracting meaningful features, and ensuring model accuracy.

    • Solutions: Implemented data augmentation techniques and advanced image processing with OpenCV. Developed and fine-tuned the Random Forest classifier, achieving high accuracy in classifying snakebite images.

    • Impact/Results: The model demonstrated the potential of machine learning in medical diagnostics and was well-received in academic circles.

    • Visuals: Include images of the dataset, feature extraction process, and performance metrics of the model.

    • Link: Snakebite Images Classification Using Random Forest Classifier

  • Description:
    During my internship at Handmadenesia, I developed a Kibana Dashboard to analyze and visualize website data for Handmadenesia.com, an e-commerce platform specializing in artisanal and handmade products. The dashboard was designed to provide real-time insights into user behavior, website traffic, sales performance, and engagement metrics, enabling the team to make data-driven decisions to optimize the website and improve the overall user experience.

    Role:
    I was responsible for configuring and deploying the Kibana Dashboard, including data indexing, visualization creation, and dashboard customization.

    Technologies Used:

    • Kibana: Used for creating and managing the interactive dashboard, including various visualizations such as line graphs, bar charts, pie charts, and heatmaps.

    • Elasticsearch: Served as the backend for storing, indexing, and querying large volumes of website data, allowing for real-time analysis and reporting.

    • Logstash: Used for data ingestion, transforming, and loading data into Elasticsearch, ensuring that the website data was correctly formatted and ready for analysis.

    Challenges:

    • Real-Time Data Monitoring: Setting up the dashboard to handle real-time data feeds, ensuring that the visualizations updated continuously as new data came in, was crucial for monitoring ongoing trends and user activities.

    • Complex Data Visualization: Translating complex e-commerce metrics, such as user journey paths, conversion rates, and sales funnels, into intuitive visualizations that were easy for the team to interpret and act upon.

    • Customization and Flexibility: Ensuring that the dashboard was customizable and flexible enough to allow team members to filter data by different parameters, such as time periods, product categories, and user segments.

    Solutions:

    • Real-Time Data Integration: I configured Elasticsearch to handle real-time data ingestion from the website, enabling the Kibana Dashboard to provide up-to-the-minute insights into site performance and user behavior.

    • Detailed Visualizations: I created a variety of visualizations in Kibana to represent key metrics, including user activity heatmaps, sales trends over time, product performance by category, and customer journey analytics. These visualizations provided actionable insights that the team could use to enhance marketing strategies and website layout.

    • User-Friendly Dashboard Design: The dashboard was designed with an intuitive layout, allowing team members to easily navigate through different sections, apply filters, and drill down into specific data points to understand underlying trends.

    Impact/Results:

    • Improved Decision-Making: The Kibana Dashboard became an essential tool for the team, providing real-time insights that informed decisions on marketing campaigns, product placement, and website improvements.

    • Enhanced User Experience: By understanding user behavior and preferences, the team was able to make targeted adjustments to the website, leading to increased user engagement and sales.

    • Scalability: The dashboard was scalable and adaptable, capable of handling increasing volumes of data as the website grew in popularity.

Skills

    • Programming Languages:

      • Python: Extensive experience in data analysis, machine learning, automation, and scripting.

      • SQL: Proficient in database management and query optimization.

      • R: Knowledgeable in statistical analysis and data visualization.

    • Data Analysis and Machine Learning:

      • Machine Learning Algorithms: Proficient in applying a wide range of machine learning algorithms, including supervised and unsupervised techniques. Experienced with decision trees, ensemble methods, and gradient boosting algorithms such as XGBoost and Random Forest.

      • Feature Engineering: Skilled in identifying and creating relevant features to improve model accuracy and performance.

      • Model Evaluation: Expertise in evaluating model performance using metrics like accuracy, precision, recall, F1 score, and AUC-ROC, ensuring robust and reliable outcomes.

      • Pandas and NumPy: Advanced skills in data manipulation and preparation, crucial for effective machine learning workflows.

      • Scikit-learn: Comprehensive experience with Scikit-learn for implementing various machine learning models and techniques.

      • PyDQC: Proficient in data quality control and validation, ensuring reliable and consistent data inputs for machine learning models.

    • Data Visualization and Reporting:

      • Matplotlib and Seaborn: Skilled in creating detailed and informative visualizations to support data-driven decision-making.

      • Kibana: Experience in building interactive dashboards for real-time data monitoring and analysis, as demonstrated in the Handmadenesia.com project.

      • Tableau: Ability to create dynamic dashboards and visual reports.

    • Tools and Technologies:

      • Git/GitHub: Version control and collaborative development.

      • Jupyter Notebook: Development and presentation of data science projects.

      • Excel: Advanced usage for data analysis, financial modeling, and reporting.

      • PyPDF2: Proficient in extracting and processing data from PDFs, as demonstrated in the Pendataan SLIK automation.

    • Analytical Thinking: Strong ability to analyze complex problems and develop effective solutions.

    • Problem-Solving: Proven track record of identifying issues and implementing innovative solutions.

    • Collaboration and Teamwork: Experience working in team settings, providing support and fostering a collaborative environment.

    • Communication: Effective communication skills, particularly in presenting technical information to non-technical stakeholders.

    • Adaptability: Quickly learns and applies new concepts and technologies to projects.

    • Attention to Detail: High level of precision in handling data and conducting analyses.

Education

Master of Data Sciences and Business Analytics, ESSEC Business School, Paris, France (currently on leave)

  • Dates: September 2023 – Present (on leave)

  • Description:

    • Pursuing an advanced degree focusing on the intersection of data science and business analytics.

    • Gained knowledge in advanced analytics, machine learning, and data-driven decision-making.

    • Currently on a leave of absence to address personal matters and seeking opportunities to apply my skills and gain further experience during this period.

Bachelor of Informatics Engineering (S1 Teknik Informatika), Telkom University, Bandung, Indonesia

  • Dates: August 2015 - August 2019

  • Relevant Coursework:

    • Machine Learning

    • Data Structures and Algorithms

    • Database Systems

    • Statistical Methods

    • Software Engineering

  • Final Project:

Certifications

Certified ScrumMaster (CSM)

  • Institution: Scrum.org

  • Date: September 2024

  • Description: Certified in Scrum methodology, with practical knowledge in leading agile projects, facilitating team collaboration, and ensuring project goals are met effectively.

Financial Modeling & Valuation Analyst (FMVA®)

  • Institution: Corporate Finance Institute (CFI)

  • Date: September 2024

  • Description: Certified in financial modeling and valuation, with expertise in building comprehensive financial models and performing detailed valuations for various types of projects and businesses.

Microsoft Technology Associate (Introduction to Programming using Python)

  • Institution: Microsoft

  • Date: July 2019

  • Description: Certification focused on foundational knowledge of Python programming, covering core concepts and practical application in programming tasks.

Machine Learning on Google Cloud

  • Institution: Google

  • Date: November 2021

  • Description: Completed certification on applying machine learning techniques using Google Cloud services, focusing on scalable and effective machine learning solutions in cloud environments.

Practical Data Science with R

  • Institution: Informit

  • Date: May 2019

  • Description: Certification focused on practical applications of data science techniques using the R programming language, including data manipulation, analysis, and visualization.

TL;DR

  • Who I Am:
    Data Scientist with nearly 4 years of experience in leveraging data to drive business growth and efficiency. Proven track record in developing innovative solutions, automating processes, and delivering impactful insights.

  • Key Achievements:

    • Owned and optimized the telemarketing leads generation model at AXA Mandiri, increasing APE by over 100%.

    • Developed three Python-based automations at BNI in just 4 weeks, including a highly praised "Pendataan SLIK" automation.

    • Created a Customer Segmentation Dashboard that enhanced marketing strategies and increased customer engagement at AXA Mandiri.

    • Developed a Kibana Dashboard for Handmadenesia.com, providing real-time insights into website performance.

  • Skills:

    • Programming Languages: Python, SQL, R

    • Machine Learning: XGBoost, Random Forest, Scikit-learn

    • Data Visualization: Matplotlib, Seaborn, Kibana

    • Certifications: Certified ScrumMaster (CSM), Financial Modeling & Valuation Analyst (FMVA®)

  • What I’m Looking For:
    Currently seeking opportunities to apply my data science expertise in impactful projects, while also continuing to learn and grow professionally.

  • Contact:
    Feel free to reach out via the contact form below or connect with me on LinkedIn.

HIT ME UP!

HIT ME UP!

"The more I learn, the more I realize how much I don't know. Yet, it is in this endless pursuit of knowledge that I find true mastery."

Phone
+6281283088057

Email

alifiando.yusuf@gmail.com