About the Role
Genpact is inviting applications for the role of AM, Machine Learning Expert - Data Science and Insights. The candidate should possess an MS in Mathematics, Computer Science, Information systems, or Computer engineering, Systems Engineering with 6+ years of relevant experience, or Computational Science or Applied Engineering industry experience in Applied Machine Learning / Predictive Analytics. Exposure to Machine Learning & Quantitative Methods in Marketing / Consumer Behavior is a must. Full cycle Real-world Analytics project experience is highly desirable: from creating a Business use case, PA assessment/roadmap, Technology & Analytic Solutioning, Implementation and Change Management.
Responsibilities
This role will primarily focus on two areas:
- Project Lead/Delivery: Lead projects, set expectations with clients/stakeholders, and ensure successful project execution.
- Solutioning: Conceptualize and develop relevant Predictive Analytic solutions for Analytic Customers. Envision opportunistic areas with clients by demonstrating relevant and credible Predictive Analytics solutions and paradigms. The role may involve carrying out high-level assessments of customer Analytics readiness and creating associated analytic benchmarking, which may ultimately converge into a client-specific Predictive Analytics roadmap.
The Manager/Senior Manager ML is expected to play a pivotal bridging role between statistical and technology specialists, and business/functional resources. Broadly, the Manager/Senior Manager shall leverage their solutioning expertise to translate customer business needs into techno-analytic problems and appropriately work with statistical & technology specialists to bring large-scale analytic solutions to fruition.
Key Roles and Responsibilities of the Manager/Senior Manager ML
- Participate in SME reviews of Predictive Analytics opportunities/engagements.
- Project Delivery: This entails successful delivery of projects involving data Pre-processing, Model Training and Evaluation, and Parameter Tuning.
- Manage Stakeholder/Customer Expectations.
- Project Blue Printing and Project Documentation.
- Creating Project Plan.
- Jump-start Machine Learning projects with customers, focusing on providing disruptive insights in reasonable timeframes.
- Actively collaborate with competency leaders in Big Data, OR, BI areas to stitch big ticket solutions with end-to-end span.
Required and Preferred Skills
Specific Competencies – Essential
Technology
- Exposure to Statistical Toolkits such as R, Weka, S-Plus, Matlab, SAS.
- Very good Python/R programming skills. Java programming skills are a plus.
- Direct involvement in working with large volumes of data and building, deploying, and measuring predictive analytics models (i.e., SVM, decision tree, clustering, logistic regression, linear and non-linear regression).
- Deep learning frameworks such as TensorFlow, Keras, Torch, Theano.
Specific Competencies – Desirable
Technology
- Understanding of GraphDB and tools such as Neo4j etc.
- Understanding of NLP, NLU, and Machine learning/Deep learning methods.
- SQL/NoSQL, MS Access, databases.
- UI development paradigms that would enable Text Mining Insights Visualization, e.g., Adobe Flex Builder, HTML5, CSS3.
- Linux, GPU Experience.
- Spark, Scala for distributed computing.
Methodology
- Previous experience with Big Data analytics implementations, using either Vanilla Hadoop or Cloudera/IBM BigInsights.
- Ability to Prioritize, Consultative mindset & Time management skills.
- Understanding/experience with the Google Cloud Platform/AWS/Azure and other Big Data solutions such as Cloudera is preferred.