Data Analyst Lead - ML Ops Engineer

Key Skills

Aartificial intelligence, Adobe Analytics, AWS, Azure, Business Analytics, Data Analysis, Data Analytics, Google Cloud Platform (GCP), Machine learning techniques, MLOps tools, NumPy, Oracle, Pandas, PySpark, Scikit-learn, SciPy, Snowflake, SQL

Job Description

• Excellent knowledge of ML algorithms (e.g., Linear Regression, Logistic Regression, Clustering/Segmentation, Decision Tree, Random Forest Algorithm, GBM, DNN, Naive Bayes, Support Vector Machine, etc.)
• Expertise in applying statistical, advanced analytics, machine learning, and/or AI, deep learning concepts, and techniques to solve business problems. Strong programming skills using Python, SQL, PySpark
• Experience with Python libraries such as Pandas, NumPy, SciPy, Scikit-Learn
• Strong analytical, critical-thinking skills with demonstrated ability to identify/analyze/synthesize data and use the data to drive decisions
• Superior communication and persuasion skills, talent for storytelling, visualization, and creating insights from data to deliver practical recommendations for business action
• Good knowledge of calculus, linear algebra, statistics, and probability
• Master’s degree in Math, Statistics, Data Science, Analytics, Econometrics, Computer science, Operations Research, Behavioral Science, or another analytical/quantitative field required

Candidates should be flexible / willing to work across this delivery landscape which includes and not limited to Agile Applications Development, Support and Deployment.

Applicants for employment in the US must have valid work authorization that does not now and/or will not in the future require sponsorship of a visa for employment authorization in the US by Capgemini.

Responsible for importing, cleaning, transforming, validating and modeling data with the purpose of understanding and drawing conclusions from data (may be presented in charts, graphs, and/or tables). Also, design and develop relational databases for collecting and storing data and build and design data input and data collection mechanisms.

Required Skills and Experience

You are responsible for data related activities such as data extraction, profiling, cleansing, de-duplication, standardization, conversion, transformation and loading, data mining, warehousing, archiving and reporting. Responsible for all activities required to ensure optimum performance and data integrity of databases in production environments, in line with the requirements. Responsible for server based databases in development and test environments including database software installation, database creation, performance and capacity design, backup and recovery design, security design.

Qualifications

• 3-7 years (2 years min relevant experience in the role) , Bachelor’s Degree.
• Should be proficient in Software Engineering Techniques, Software Engineering Architecture, Software Engineering Lifecycle and Data Management.
• Should have progressing skills in Business Analysis, Business Knowledge, Software Engineering Leadership, Architecture Knowledge and Technical Solution Design.

In a world where change happens in a split second, our clients must master the art of balancing business transformation with operational excellence and cost reduction to protect their market leadership and safeguard their workforce.

They need the best and brightest talent to limit business disruption and foster future growth, all while striving to realize a new normal. In this context, it’s our people within Insights & Data that are the core enablers to support our clients in their growth journeys. To give our clients our best and brightest, we pride ourselves on being a fast-paced, fun, ethical place to work, where the “work hard, play hard” mentality holds true. Even more important is our clear commitment to creating a diverse workforce in all areas. In fact, for the ninth time in a row, Capgemini has been recognized as one of the World’s Most Ethical Companies by the Ethisphere Institute. In addition, we’ve been recognized as a top company for women by Working Mother Media.