DeepIntent

What You’ll Do:

We are looking for a Staff Operations 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 Engineering Operations team 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 standardize all interface points for analysts to retrieve and analyze data with a focus on research methodologies and data-based decision-making.
• Optimize queries and data access efficiencies, serve as an expert in how to most efficiently attain desired data points.
• Build “mastered” versions of the data for Analytics-specific querying use cases.
• Establish a formal data practice for the Analytics practice in conjunction with the rest of DeepIntent.
• Interpret analytics methodology requirements and apply them 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, and analysts.
• Operate between Engineers and Analysts to unify both practices for analytics insight creation.

Who You Are:

• 8+ years of experience in Tech Support (Specialised in Monitoring and maintaining Data pipeline).
• 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 the ability to collaborate and translate 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.
• 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.
• Experience in debugging UI and Backend issues will be add on.

What You’ll Do:

As a Sr. Data Scientist, you will work closely across DeepIntent Data Science teams located in New York, India, and Bosnia. The role will focus on building predictive models, implementing data-driven solutions to maximize ad effectiveness. You will also lead efforts in generating analyses and insights related to the measurement of campaign outcomes, Rx, patient journey, and supporting the evolution of the DeepIntent product suite. Activities in this position include developing and deploying models in production, reading campaign results, analyzing medical claims, clinical, demographic and clickstream data, performing analysis and creating actionable insights, summarizing, and presenting results and recommended actions to internal stakeholders and external clients, as needed.

• Explore ways to create better predictive models.
• Analyze medical claims, clinical, demographic and clickstream data to produce and present actionable insights.
• Explore ways of using inference, statistical, and machine learning techniques to improve the performance of existing algorithms and decision heuristics.
• Design and deploy new iterations of production-level code.
• Contribute posts to our upcoming technical blog.

Who You Are:

• Bachelor’s degree in a STEM field, such as Statistics, Mathematics, Engineering, Biostatistics, Econometrics, Economics, Finance, or Data Science.
• 5+ years of working experience as a Data Scientist or Researcher in digital marketing, consumer advertisement, telecom, or other areas requiring customer-level predictive analytics.
• Advanced proficiency in performing statistical analysis in Python, including relevant libraries, is required.
• Experience working with data processing, transformation and building model pipelines using tools such as Spark, Airflow, and Docker.
• You have an understanding of the ad-tech ecosystem, digital marketing and advertising data and campaigns or familiarity with the US healthcare patient and provider systems (e.g. medical claims, medications).
• You have varied and hands-on predictive machine learning experience (deep learning, boosting algorithms, inference…).
• You are interested in translating complex quantitative results into meaningful findings and interpretable deliverables, and communicating with less technical audiences orally and in writing.
• You can write production level code, work with Git repositories.
• Active Kaggle participant.
• Working experience with SQL.
• Familiar with medical and healthcare data (medical claims, Rx, preferred).
• Conversant with cloud technologies such as AWS or Google Cloud.

What You’ll Do:

• Setting up formal data practices for the company.
• Building and running super stable and scalable data architectures.
• Making it easy for folks to add and use new data with self-service pipelines.
• Getting DataOps practices in place.
• Designing, developing, and running data pipelines to help out Products, Analytics, data scientists and machine learning engineers.
• Creating simple, reliable data storage, ingestion, and transformation solutions that are a breeze to deploy and manage.
• Writing and Managing reporting API for different products.
• Implementing different methodologies for different reporting needs.
• Teaming up with all sorts of people – business folks, other software engineers, machine learning engineers, and analysts.

Who You Are:

• Bachelor’s degree in engineering (CS / IT) or equivalent degree from a well-known Institute / University.
• 3.5+ years of experience in building and running data pipelines for tons of data.
• Experience with public clouds like GCP or AWS.
• Experience with Apache open-source projects like Spark, Druid, Airflow, and big data databases like BigQuery, Clickhouse.
• Experience making data architectures that are optimised for both performance and cost.
• Good grasp of software engineering, DataOps, data architecture, Agile, and DevOps.
• Proficient in SQL, Java, Spring Boot, Python, and Bash.
• Good communication skills for working with technical and non-technical people.
• Someone who thinks big, takes chances, innovates, dives deep, gets things done, hires and develops the best, and is always learning and curious.