Data Scientist Job in Capgemini

As a Data Scientist at Capgemini Invent, you will be at the forefront of solving complex business problems by utilizing data analytics, machine learning, and deep learning techniques. Your work will involve processing large datasets, mining data for insights, and developing robust analytical solutions. You will work closely with clients to understand their business challenges and provide data-driven strategies for success.

Key Responsibilities:

• Business Requirement Analysis: Collaborate with clients to understand business needs and design appropriate data-driven solutions to address their challenges.

• Data Processing and Integrity: Process, clean, and verify the integrity of data used for analysis, ensuring high-quality data for accurate insights.

• Exploratory Data Analysis (EDA): Use advanced methods for data mining and perform exploratory data analysis (EDA) to uncover trends, patterns, and correlations in datasets.

• Machine Learning & Deep Learning: Select relevant features and build/optimize classifiers or regressors using machine learning and deep learning techniques (e.g., k-NN, Regression, SVM, Random Forests, PCA, GenAI).

• Data Collection Enhancement: Collaborate to enhance data collection processes, ensuring that all necessary information is captured for robust analytics and modeling.

• Ad-Hoc Analysis & Reporting: Perform ad-hoc analysis as required, presenting results clearly to stakeholders and guiding decision-making.

• Analytics-Delivery Procedures: Contribute to the improvement of analytics-delivery procedures, ensuring all work is well-documented and follows best practices.

Your Profile:

• Strong Problem-Solving Abilities: A passion for solving business problems through data, with a focus on using data analytics and machine learning as core tools.

• Experience in Data & Analytics Solutions: Experience delivering data & analytics solutions in one or more of the following areas:

  • Machine Learning
  • Predictive Analytics
  • Statistical Modeling

• Programming Skills: Proficiency in coding languages commonly used in data science, such as Python, R, Go, SAS, or Matlab.

• Data Science Toolkits: Experience with essential data science libraries and frameworks, including:

  • NumPy, Pandas, SciPy
  • Scikit-learn, TensorFlow, PyTorch
  • NLTK, Spacy, OpenCV
  • MLFlow, Gensim

• Database Management: Hands-on experience with querying languages such as SQL, NoSQL, and other database technologies.

• Machine Learning & Algorithms Expertise: Strong understanding of machine learning techniques and algorithms for both supervised and unsupervised problems (e.g., k-NN, Naive Bayes, SVM, Decision Trees, k-means, PCA, LLMs).

• Statistics & Inference: Good knowledge of applied statistics, including distributions, statistical inference, and hypothesis testing.

• Cloud Platforms: Familiarity with cloud platforms (AWS, Azure, GCP) and their integration with data science workflows.

What You Will Love About Working Here:

• Flexible Work Arrangements: Embrace a healthy work-life balance with flexible work hours and the possibility of remote work options.

• Career Growth: At Capgemini, your career development is a priority. We offer diverse growth programs and provide you with opportunities to explore a wide range of career paths within our global network.

• Cutting-Edge Technologies: Stay ahead of the curve by working with the latest advancements in technology, including Generative AI and other emerging trends.