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Job Description:

We are searching for the best talent for Machine Learning Engineer.

As a Data Science / ML Engineer at J& J, you will collaborate closely with stakeholders across various functions to develop innovative Data Science solutions addressing diverse business challenges. From feasibility studies to deployment, you' ll be involved in the entire lifecycle—from understanding pain points to transforming data into impactful insights and scalable models.

You will be responsible for

• Partnering with stakeholders to understand their business problems and define data-driven solutions.
• Conducting feasibility studies by engaging with stakeholders to capture pain points and relevant use cases.
• Extracting and collecting data from databases and other sources in collaboration with Data Engineers and IT teams.
• Cleaning, preprocessing, and standardizing data to ensure quality and usability.
• Researching appropriate solutions by reviewing literature on statistical and machine learning methodologies, exploring Python libraries, and evaluating available models such as LLMs.
• Performing feature engineering to build predictors/variables vital for model accuracy.
• Coding solutions using Python within analytics platforms like Databricks.
• Communicating findings and solutions to stakeholders; iteratively refine models based on testing and validation.
• Deploying models in analytics platforms, working with Software Developers on frontend designs for real-time predictions or Data Visualization specialists for batch/scheduled forecasts using tools like Tableau or PowerBI.
• Collaborating with Data Engineers to deploy backend pipelines supporting these solutions.

Qualifications / Requirements :

• At least 2 years of experience in Data Science, Data Analytics, Statistical Modeling, Machine Learning Engineering, or related roles.
• Bachelor’s or Master’s degree in Statistics, Physics, Computer Science, Engineering, Mathematics, Economics, or a similar field.
• Proficient in Python, with experience using libraries such as statsmodels, TensorFlow, PyTorch, etc., especially for statistical modeling, machine/deep learning, and handling big data.
• Knowledge of Large Language Models (LLMs) for Natural Language Processing
• Knowledge on Statistical and Machine Learning modeling (such as clustering, regression modeling, time series modeling, etc.).
• Experience with SQL and data manipulation techniques.
• Familiarity with analytics platforms such as Databricks, Domino, Dataiku, etc.
• Familiarity with dashboard and visualization tools like Tableau and Power BI.
• Willingness to work on a mid shift