3+ EMR Jobs in Chennai | EMR Job openings in Chennai

Responsibilities:

 Understand needs and requirements; build a strong relationship with doctors
 Visit the assigned market territory to conduct demos for users (doctors) and manage
deal closure
 Building sales pipeline by acquiring new and converting competition user
 Rigorous & structured follow-ups with Doctors to ensure sales closure
 Provide in-depth platform training to the doctors and clinic staff
 Close sales and achieve monthly and quarterly targets
 Maintain and expand your database of prospects through referral channel

Requirements:

 Excellent communication skills(English & Regional language preferred) with a focus
on driving a sales
 Plan and travel extensively across the assigned territory & upcountry if required
 Strong people skills with high customer-centricity
 Good technical understanding of the product
 Strong listening, presentation & time management skills
 Any bachelor's / Master's degree (Biotech/Pharma will be preferred)

Perks and Benefits

 Lucrative monthly incentive and R&R programs
 Free medical insurance from the company
 Salary (CTC) starts from 3 Lakh Fixed plus 3 Lakh Variable
 Day shift (10.30 am to 7.30 pm)
 6 days Work 1 day off (Sunday)

HCC Documentation and coding. AAPC / AHIMA Certification. Knowledge of EMR for reviewing records. Analytical skills

We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.

 

Skills:

- 5+ years deploying Machine Learning pipelines in large enterprise production systems.

- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.

 

Roles and Responsibilities:

Deploying ML models into production, and scaling them to serve millions of customers.

Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.

Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.

Provide software design and programming support to projects.

 

 Qualifications & Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.