Job Description:
We are seeking an experienced and highly analytical Data Scientist with a strong background in Machine Learning and Visualization to join our dynamic team. You will be instrumental in leveraging our rich datasets to uncover insights, build sophisticated predictive models, and create impactful visualizations that drive strategic decisions.
Responsibilities:
- Own the end-to-end lifecycle of data science projects, from defining the business problem and exploring data to developing, validating, deploying, and monitoring models in production.
- Understand Business Problems and Apply advanced statistical methodologies and machine learning algorithms to analyze large, complex datasets (structured and unstructured) and extract meaningful patterns and insights aligned to Objective.
- Develop and implement robust, scalable, and automated processes for data analysis and model pipelines, leveraging Google cloud infrastructure.
- Collaborate closely with business stakeholders and cross-functional teams to understand their analytical needs, translate them into technical requirements, and effectively communicate findings.
- Create compelling and interactive dashboards and data visualizations to clearly articulate the complex results and insights to both technical and non-technical audiences.
- Stay up to date with the latest advancements in machine learning, and cloud technologies, and advocate for the adoption of best practices.
Technical Requirements:
- 4+ years of relevant, progressive professional experience in a Data Scientist, Machine Learning Engineer, or similar role, with a track record of successfully delivering data science projects.
- Bachelor's or master's degree with a strong foundation in Statistics & Probability, Machine Learning and Deep Learning (Supervised & Unsupervised).
- Proven hands-on experience applying a variety of machine learning techniques (e.g., regression, classification, clustering, tree-based models, potentially deep learning) to real-world business problems.
- Must have strong proficiency in Python and its data science ecosystem (e.g., Pandas, NumPy, Scikit-learn, potentially TensorFlow or PyTorch).
- Hands-on experience working with cloud computing platforms (e.g., GCP(preferred) AWS, Azure) for data storage, processing, and deploying analytical solutions.
- Extensive experience creating data visualizations and dashboards (e.g., Power-BI & Looker, Dash) to effectively communicate insights. You know how to tell a story with data!
- Solid understanding of experimental design, hypothesis testing, and statistical inference.
- Excellent problem-solving skills, attention to detail, and the ability to work with complex data structures.
- Strong communication, presentation, and interpersonal skills, with the ability to explain technical concepts clearly to diverse audiences.
Good to Have:
- Experience working within the Automotive industry or with related data such as vehicle telematics, manufacturing quality, supply chain, or customer behaviour in an automotive context.
- Experience with GCP services such as GCP Big query, GCS, Cloud Run, Cloud Build, Cloud Source Repositories, Cloud Workflows
- Experience with Generative AI and LLM Models
- Proficiency with specific dashboarding and visualization tools such as Looker Studio, Power Bi, Qlik.
- Experience with SQL for data querying and manipulation.
- Familiarity with big data technologies (e.g., Spark, Hadoop).
- Experience with MLOps practices and tools for deploying and managing models in production.
Soft Skills:
- Strong communication and collaboration skills
- Ability to work in a fast-paced, agile environment
- Proactive attitude and start-up mindset
