Multiple Postion

Hi,

 

Greetings from Diamondpick! 

 

This is Dinesh Ashwin, and we have openings for Multiple Position. I have given the JD below please have a look and if you are interested kindly share me their updated resume and available time to discuss further.

               

1.       Position: Business Analyst (with Payments)

Location: Jersey City/ Plano, TX

Client: Mphasis /JPMC

Experience: 8 + years

 

Skills: Payments Processing Experience.

Job Description:

Graphite (Wholesale Payments) – Good to have

·         Minimum 10+ years of experience working in the role of Payments SME / Payments BSA.

·         Good experience in Payments Functional solutioning & designing.

·         Exposure to end-to-end lifecycle of Retail & Wholesale Payments.

·         Good knowledge of global trends in Payment’s industry.

·         Exposure to multiple Global Market Infrastructures - ACH, Fedwire, CHIPS, CHAPS, FPS, RTP, SEPA (Direct Debits, Credit Transfers, Mandate Management), TARGET2, IMPS and Message formats - ISO20022 & SWIFT

·         Hands on experience in grounds up development of Global Payments platform or Payment’s products like Finastra-GPP, ACI-UPP, etc.

·         Preferred - Experience in multi-country implementation of Payment Hub / Payments Platform at large banks.

·         Should be self-starter and highly energetic.

·         Excellent verbal and written communication skills.

·         Strong analytical skills.

 

 

2.       Position: ML (Machine Learning) Engineer & Devops

Location: Jersey City/ Chicago, IL

Client: Mphasis /JPMC

Experience: 8 + years

 

Job Description:

The client expects you to apply sophisticated machine learning methods to a wide variety of tasks.  Must be willing to work in a highly collaborative environment together with the business, technologists and control partners to deploy solutions into production.  The candidate must also have a strong passion for machine learning and invest independent time towards learning, researching and experimenting with new innovations in the field. 

The candidate must have solid expertise in Deep Learning with hands-on implementation experience and possess strong analytical thinking, a deep desire to learn and be highly motivated.

 

Responsibilities

·         Research and explore new machine learning methods through independent study, experimentation and participating in our knowledge sharing community

·         Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as NLP, speech recognition, time-series predictions or recommendation systems

·         Lead your own project, from feasibility assessment and research through to model development

·         Perform predictive modeling, machine learning, statistical modeling, large scale data acquisition, transformation, and cleaning, both structured and unstructured data

·         Use DevOps / leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.

 

Minimum Qualifications

·         Hands-on 5Years + experience and solid understanding of machine learning and deep learning methods

·         Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.

·         Strong Python programing skills with Pandas- Fuzzy Wuzzy/Flask/SKlearn, NumPy  /unit test

·         Extensive experience with machine learning and deep learning toolkits ((e.g. scikit-learn, OmniAI, MLR, TensorFlow, CNTK, MLlib))

·         Scientific thinking and the ability to invent

·         Construct optimized data pipelines to feed ML models.

·         Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals

·         Experience with big data and scalable model training

·         Leverage cloud-based architectures and technologies to deliver optimized ML models at scale.

·         Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences

·         Curious, hardworking and detail-oriented, and motivated by complex analytical problems

·         Ability to work both independently and in highly collaborative team environments

·         Knowledge in Reinforcement Learning or Meta Learning

·         Ability to develop and debug production-quality code

·         Familiarity with continuous integration models and unit test development

·         Familiarity with the financial services industry

·         Very good querying skills on Oracle for feature creation

 

Preferred Qualifications:

·         Applied experience building, scaling, and optimizing ML systems.

·         At least 2 years of experience developing performant, resilient, and maintainable code.

·         Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform.

·         Exposure to AWS is an added advantage

·         At least 3 years of experience building production-ready data pipelines that feed ML models.

·         Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance.

 

 

 

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