Data Scientist

Analytical professional who uses statistical methods, machine learning, and programming skills to extract insights and knowledge from data. Their primary goal is to solve complex business problems, make predictions, and drive strategic decision-making by uncovering patterns and trends within large datasets.

In this role, you will embark on a transformative process of business understanding, data understanding, and data preparation. Utilizing statistical and mathematical modeling techniques, you'll have the opportunity to create models that defy convention - models that hold the key to solving intricate business challenges. With an acute eye for accuracy and generalization, you'll evaluate these models to ensure they not only solve business problems but do so optimally.

Additionally, you're not just building and validating models - you're deploying them as code to applications and processes, ensuring that the model(s) you've selected sustains its business value throughout its lifecycle.

Your expertise doesn't stop at data; you'll become intimately familiar with our business processes and have the ability to navigate their complexities, identifying issues and crafting solutions that drive meaningful change in these domains. You will develop and apply standards and policies that protect our organization's most valuable asset - ensuring that data is secure, private, accurate, available, and, most importantly, usable. Your mastery extends to data management, migration, strategy, change management, and policy and regulation.

Key Responsibilities:

• Problem Framing: Collaborating with stakeholders to understand business problems and translate them into data-driven questions.

• Data Collection and Cleaning: Sourcing, collecting, and cleaning large, often messy, datasets from various sources, preparing them for analysis.

• Exploratory Data Analysis (EDA): Performing initial investigations on data to discover patterns, spot anomalies, test hypotheses, and check assumptions with the help of summary statistics and graphical representations.

• Model Development: Building, training, and validating machine learning models (e.g., regression, classification, clustering, deep learning) to predict outcomes or identify relationships.

• Statistical Analysis: Applying statistical tests and methodologies to draw robust conclusions from data and quantify uncertainty.

• Feature Engineering: Creating new variables or transforming existing ones to improve model performance and provide deeper insights.

• Model Deployment: Working with engineering teams to deploy models into production environments, making them operational for real-time predictions or insights.

• Communication and Storytelling: Presenting complex findings and recommendations clearly and concisely to both technical and non-technical audiences, often through visualizations and narratives.

• Monitoring and Maintenance: Tracking model performance in production and updating models as data patterns evolve or new data becomes available.

If you're ready to embrace the power of data to transform our business and embark on an epic data adventure, then join us at Kyndryl. Together, let's redefine what's possible and unleash your potential.

Your Future at Kyndryl
Every position at Kyndryl offers a way forward to grow your career. We have opportunities that you won't find anywhere else, including hands-on experience, learning opportunities, and the chance to certify in all four major platforms. Whether you want to broaden your knowledge base or narrow your scope and specialize in a specific sector, you can find your opportunity here.

Who You Are

You're good at what you do and possess the required experience to prove it. However, equally as important - you have a growth mindset; keen to drive your own personal and professional development. You are customer-focused - someone who prioritizes customer success in their work. And finally, you're open and borderless - naturally inclusive in how you work with others.

Required Technical and Professional Expertise

• 8 - 10 years of experience as an Data Scientist .
• Programming Languages: Strong proficiency in Python and/or R, with libraries for data manipulation (e.g., Pandas, dplyr), scientific computing (e.g., NumPy), and machine learning (e.g., Scikit-learn, TensorFlow, PyTorch).
• Statistics and Probability: A solid understanding of statistical inference, hypothesis testing, probability distributions, and experimental design.
• Machine Learning: Deep knowledge of various machine learning algorithms, their underlying principles, and when to apply them.
• Database Querying: Proficiency in SQL for extracting and manipulating data from relational databases.
• Data Visualization: Ability to create compelling and informative visualizations using tools like Matplotlib, Seaborn, Plotly, or Tableau.
• Big Data Concepts: Familiarity with concepts and tools for handling large datasets, though often relying on Data Engineers for infrastructure.
• Domain Knowledge: Understanding of the specific industry or business domain to contextualize data and insights.

Preferred Technical and Professional Experience

• Degree in a scientific discipline, such as Computer Science, Software Engineering, or Information Technology

Being You

Diversity is a whole lot more than what we look like or where we come from, it's how we think and who we are. We welcome people of all cultures, backgrounds, and experiences. But we're not doing it single-handily: Our Kyndryl Inclusion Networks are only one of many ways we create a workplace where all Kyndryls can find and provide support and advice. This dedication to welcoming everyone into our company means that Kyndryl gives you - and everyone next to you - the ability to bring your whole self to work, individually and collectively, and support the activation of our equitable culture. That's the Kyndryl Way.

What You Can Expect

With state-of-the-art resources and Fortune 100 clients, every day is an opportunity to innovate, build new capabilities, new relationships, new processes, and new value. Kyndryl cares about your well-being and prides itself on offering benefits that give you choice, reflect the diversity of our employees and support you and your family through the moments that matter - wherever you are in your life journey. Our employee learning programs give you access to the best learning in the industry to receive certifications, including Microsoft, Google, Amazon, Skillsoft, and many more. Through our company-wide volunteering and giving platform, you can donate, start fundraisers, volunteer, and search over 2 million non-profit organizations. At Kyndryl, we invest heavily in you, we want you to succeed so that together, we will all succeed.

Get Referred!

If you know someone that works at Kyndryl, when asked 'How Did You Hear About Us' during the application process, select 'Employee Referral' and enter your contact's Kyndryl email address.