• Job Description

  Req#: 44994

  Potential candidates should have excellent depth and breadth of knowledge in machine learning, data mining, statistical modeling and Generative AI. They should possess the ability to translate a business problem into an analytical problem, identify the relevant data sets needed for addressing the analytical problem, recommend, implement, and validate the best suited analytical algorithm(s), and generate/deliver insights to stakeholders. Candidates are expected to be at the cutting-edge with respect to algorithms, tools, and techniques and have excellent business acumen and communication, focusing on delivering business value. The role is that of an individual contributor; however, the candidate is expected to work in project teams of 2 to 3 people and interact with business partners on regular basis.

  Qualifications

  • Bachelor’s degree in computer science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline.
  • 2+ years of hands-on experience in Python programming for data analysis, machine learning, and with libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch, NLTK, spaCy, and Gensim.
  • 2+ years of experience with both supervised and unsupervised machine learning techniques.
  • 2+ years of experience with data analysis and visualization using Python packages such as Pandas, NumPy, Matplotlib, Seaborn, or data visualization tools like Dash or QlikSense.
  • 1+ years' experience in SQL programming language and relational databases.
  • 2+ years experience in any dashboarding tool such as Tableau, Power BI, DOMO and QlikSense

  Preferred Qualifications

  • An MS/PhD in Computer Science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. PhD strongly preferred.
  • Experience working with Google Cloud Platform (GCP) services, leveraging its capabilities for ML model development and deployment.
  • Experience with Git and GitHub for version control and collaboration.
  • Besides Python, familiarity with one more additional programming language (e.g., C/C++/Java)
  • Strong background and understanding of mathematical concepts relating to probabilistic models, conditional probability, numerical methods, linear algebra, neural network under the hood detail.
  • Experience working with large language models such GPT-4, Google, Palm, Llama-2, etc.
  • Excellent problem solving, communication, and data presentation skills.

  Responsibilities

  • Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making
  • Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data-driven decision-making
  • Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends
  • Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation
  • Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness

• About the company

  Ford is a global company with shared ideals and a deep sense of family. From our earliest days as a pioneer of modern transportation.

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