Senior Data Scientist

Who We Are:

DeepIntent is leading the healthcare advertising industry with data-driven solutions built for the future. From day one, our mission has been to improve patient outcomes through the artful use of advertising, data science, and real-world clinical data.

What You’ll Do:

We are looking for a Senior Software Engineer based in Pune, India who can master both DeepIntent’s data architectures and pharma research and analytics methodologies to make significant contributions to how health media is analyzed by our clients. This role requires an Engineer who not only understands DBA functions but also how they impact research objectives and can work with researchers and data scientists to achieve impactful results.  

This role will be in the Analytics Organization and will require integration and partnership with the Engineering Organization. The ideal candidate is a self-starter who is inquisitive who is not afraid to take on and learn from challenges and will constantly seek to improve the facets of the business they manage. The ideal candidate will also need to demonstrate the ability to collaborate and partner with others.  

• Serve as the Engineering interface between Analytics and Engineering teams
• Develop and standardized all interface points for analysts to retrieve and analyze data with a focus on research methodologies and data based decisioning
• Optimize queries and data access efficiencies, serve as expert in how to most efficiently attain desired data points
• Build “mastered” versions of the data for Analytics specific querying use cases
• Help with data ETL, table performance optimization
• Establish formal data practice for the Analytics practice in conjunction with rest of DeepIntent
• Build & operate scalable and robust data architectures
• Interpret analytics methodology requirements and apply to data architecture to create standardized queries and operations for use by analytics teams
• Implement DataOps practices
• Master existing and new Data Pipelines and develop appropriate queries to meet analytics specific objectives
• Collaborate with various business stakeholders, software engineers, machine learning engineers, analysts
• Operate between Engineers and Analysts to unify both practices for analytics insight creation

Who You Are:

• Adept in market research methodologies and using data to deliver representative insights
• Inquisitive, curious, understands how to query complicated data sets, move and combine data between databases
• Deep SQL experience is a must
• Exceptional communication skills with ability to collaborate and translate with between technical and non technical needs
• English Language Fluency and proven success working with teams in the U.S.
• Experience in designing, developing and operating configurable Data pipelines serving high volume and velocity data
• Experience working with public clouds like GCP/AWS
• Good understanding of software engineering, DataOps, and data architecture, Agile and DevOps methodologies
• Experience building Data architectures that optimize performance and cost, whether the components are prepackaged or homegrown
• Proficient with SQL,Python or JVM based language, Bash
• Experience with any of Apache open source projects such as Spark, Druid, Beam, Airflow etc.and big data databases like BigQuery, Clickhouse, etc         
• Ability to think big, take bets and innovate, dive deep, hire and develop the best talent, learn and be curious
• Comfortable to work in EST Time Zone

• 6+ years Experienced in building data pipelines and deployment pipelines for machine learning models
• 4+ years’ experience with ML/AI toolkits such as Tensorflow, Keras, AWS Sagemaker, MXNet, H20, etc.
• 4+ years’ experience developing ML/AI models in Python/R
• Must have leadership abilities to lead a project and team.
• Must have leadership skills to lead and deliver projects, be proactive, take ownership, interface with business, represent the team and spread the knowledge.
• Strong knowledge of statistical data analysis and machine learning techniques (e.g., Bayesian, regression, classification, clustering, time series, deep learning).
• Should be able to help deploy various models and tune them for better performance.
• Working knowledge in operationalizing models in production using model repositories, API s and data pipelines.
• Experience with machine learning and computational statistics packages.
• Experience with Data Bricks, Data Lake.
• Experience with Dremio, Tableau, Power Bi.
• Experience working with spark ML, spark DL with Pyspark would be a big plus!
• Working knowledge of relational database systems like SQL Server, Oracle.
• Knowledge of deploying models in platforms like PCF, AWS, Kubernetes.
• Good knowledge in Continuous integration suites like Jenkins.
• Good knowledge in web servers (Apache, NGINX).
• Good knowledge in Git, Github, Bitbucket.
• Working knowledge in operationalizing models in production using model repositories, APIs and data pipelines.
• Java, R, and Python programming experience.
• Should be very familiar with (MS SQL, Teradata, Oracle, DB2).
• Big Data – Hadoop.
• Expert knowledge using BI tools e.g.Tableau
• Experience with machine learning and computational statistics packages.

We are #hiring for AWS Data Engineer expert to join our team

Job Title: AWS Data Engineer

Experience: 5 Yrs to 10Yrs

Location: Remote

Notice: Immediate or Max 20 Days

Role: Permanent Role

Skillset: AWS, ETL, SQL, Python, Pyspark, Postgres DB, Dremio.

Job Description:

 Able to develop ETL jobs.

Able to help with data curation/cleanup, data transformation, and building ETL pipelines.

Strong Postgres DB exp and knowledge of Dremio data visualization/semantic layer between DB and the application is a plus.

Sql, Python, and Pyspark is a must.

Communication should be good

Job Summary

As a Data Science Lead, you will manage multiple consulting projects of varying complexity and ensure on-time and on-budget delivery for clients. You will lead a team of data scientists and collaborate across cross-functional groups, while contributing to new business development, supporting strategic business decisions and maintaining & strengthening client base

1. Work with team to define business requirements, come up with analytical solution and deliver the solution with specific focus on Big Picture to drive robustness of the solution
2. Work with teams of smart collaborators. Be responsible for their appraisals and career development.
3. Participate and lead executive presentations with client leadership stakeholders.
4. Be part of an inclusive and open environment. A culture where making mistakes and learning from them is part of life
5. See how your work contributes to building an organization and be able to drive Org level initiatives that will challenge and grow your capabilities.

​​​​​​Role & Responsibilities

1. Serve as expert in Data Science, build framework to develop Production level DS/AI models.
2. Apply AI research and ML models to accelerate business innovation and solve impactful business problems for our clients.
3. Lead multiple teams across clients ensuring quality and timely outcomes on all projects.
4. Lead and manage the onsite-offshore relation, at the same time adding value to the client.
5. Partner with business and technical stakeholders to translate challenging business problems into state-of-the-art data science solutions.
6. Build a winning team focused on client success. Help team members build lasting career in data science and create a constant learning/development environment.
7. Present results, insights, and recommendations to senior management with an emphasis on the business impact.
8. Build engaging rapport with client leadership through relevant conversations and genuine business recommendations that impact the growth and profitability of the organization.
9. Lead or contribute to org level initiatives to build the Tredence of tomorrow.

Qualification & Experience

1. Bachelor's /Master's /PhD degree in a quantitative field (CS, Machine learning, Mathematics, Statistics, Data Science) or equivalent experience.
2. 6-10+ years of experience in data science, building hands-on ML models
3. Expertise in ML – Regression, Classification, Clustering, Time Series Modeling, Graph Network, Recommender System, Bayesian modeling, Deep learning, Computer Vision, NLP/NLU, Reinforcement learning, Federated Learning, Meta Learning.
4. Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Support Vector Machines ANOVA , Principal Component Analysis, Gradient Boosted Trees, ANN, CNN, RNN, Transformers.
5. Knowledge of programming languages SQL, Python/ R, Spark.
6. Expertise in ML frameworks and libraries (TensorFlow, Keras, PyTorch).
7. Experience with cloud computing services (AWS, GCP or Azure)
8. Expert in Statistical Modelling & Algorithms E.g. Hypothesis testing, Sample size estimation, A/B testing
9. Knowledge in Mathematical programming – Linear Programming, Mixed Integer Programming etc , Stochastic Modelling – Markov chains, Monte Carlo, Stochastic Simulation, Queuing Models.
10. Experience with Optimization Solvers (Gurobi, Cplex) and Algebraic programming Languages(PulP)
11. Knowledge in GPU code optimization, Spark MLlib Optimization.
12. Familiarity to deploy and monitor ML models in production, delivering data products to end-users.
13. Experience with ML CI/CD pipelines.

1. Expertise in building AWS Data Engineering pipelines with AWS Glue -> Athena -> Quick sight
2. Experience in developing lambda functions with AWS Lambda
3. Expertise with Spark/PySpark – Candidate should be hands on with PySpark code and should be able to do transformations with Spark
4. Should be able to code in Python and Scala.
5. Snowflake experience will be a plus