Ab>initio, Big Data, Informatica, Tableau, Data Architect, Cognos, Microstrategy, Healther Business Analysts, Cloud etc.

We’re seeking a highly skilled, execution-focused Senior Data Scientist with a minimum of 5 years of experience. This role demands hands-on expertise in building, deploying, and optimizing machine learning models at scale, while working with big data technologies and modern cloud platforms. You will be responsible for driving data-driven solutions from experimentation to production, leveraging advanced tools and frameworks across Python, SQL, Spark, and AWS. The role requires strong technical depth, problem-solving ability, and ownership in delivering business impact through data science.

Responsibilities

• Design, build, and deploy scalable machine learning models into production systems.
• Develop advanced analytics and predictive models using Python, SQL, and popular ML/DL frameworks (Pandas, Scikit-learn, TensorFlow, PyTorch).
• Leverage Databricks, Apache Spark, and Hadoop for large-scale data processing and model training.
• Implement workflows and pipelines using Airflow and AWS EMR for automation and orchestration.
• Collaborate with engineering teams to integrate models into cloud-based applications on AWS.
• Optimize query performance, storage usage, and data pipelines for efficiency.
• Conduct end-to-end experiments, including data preprocessing, feature engineering, model training, validation, and deployment.
• Drive initiatives independently with high ownership and accountability.
• Stay up to date with industry best practices in machine learning, big data, and cloud-native deployments.

Requirements:

• Minimum 5 years of experience in Data Science or Applied Machine Learning.
• Strong proficiency in Python, SQL, and ML libraries (Pandas, Scikit-learn, TensorFlow, PyTorch).
• Proven expertise in deploying ML models into production systems.
• Experience with big data platforms (Hadoop, Spark) and distributed data processing.
• Hands-on experience with Databricks, Airflow, and AWS EMR.
• Strong knowledge of AWS cloud services (S3, Lambda, SageMaker, EC2, etc.).
• Solid understanding of query optimization, storage systems, and data pipelines.
• Excellent problem-solving skills, with the ability to design scalable solutions.
• Strong communication and collaboration skills to work in cross-functional teams.

Benefits:

• Best in class salary: We hire only the best, and we pay accordingly.
• Proximity Talks: Meet other designers, engineers, and product geeks — and learn from experts in the field.
• Keep on learning with a world-class team: Work with the best in the field, challenge yourself constantly, and learn something new every day.

About Us:

Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media, and Entertainment companies in the world! We’re headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore. Since 2019, Proximity has created and grown high-impact, scalable products used by 370 million daily users, with a total net worth of $45.7 billion among our client companies.

Today, we are a global team of coders, designers, product managers, geeks, and experts. We solve complex problems and build cutting-edge tech, at scale. Our team of Proxonauts is growing quickly, which means your impact on the company’s success will be huge. You’ll have the chance to work with experienced leaders who have built and led multiple tech, product, and design teams.

Job Description:

The data science team is responsible for solving business problems with complex data. Data complexity could be characterized in terms of volume, dimensionality and multiple touchpoints/sources. We understand the data, ask fundamental-first-principle questions, apply our analytical and machine learning skills to solve the problem in the best way possible. 

Our ideal candidate

The role would be a client facing one, hence good communication skills are a must. 

The candidate should have the ability to communicate complex models and analysis in a clear and precise manner. 

The candidate would be responsible for:

• Comprehending business problems properly - what to predict, how to build DV, what value addition he/she is bringing to the client, etc.
• Understanding and analyzing large, complex, multi-dimensional datasets and build features relevant for business
• Understanding the math behind algorithms and choosing one over another
• Understanding approaches like stacking, ensemble and applying them correctly to increase accuracy

Desired technical requirements

• Proficiency with Python and the ability to write production-ready codes. 
• Experience in pyspark, machine learning and deep learning
• Big data experience, e.g. familiarity with Spark, Hadoop, is highly preferred
• Familiarity with SQL or other databases.

• Act as primary day-to-day contact on analytics to agency-client leads
• Develop bespoke analytics proposals for presentation to agencies & clients, for delivery within the teams
• Ensure delivery of projects and services across the analytics team meets our stakeholder requirements (time, quality, cost)
• Hands on platforms to perform data pre-processing that involves data transformation as well as data cleaning
  
• Ensure data quality and integrity
  
• Interpret and analyse data problems
  
• Build analytic systems and predictive models
  
• Increasing the performance and accuracy of machine learning algorithms through fine-tuning and further
  
• Visualize data and create reports
  
• Experiment with new models and techniques
  
• Align data projects with organizational goals

• Min 6 - 7 years’ experience working in Data Science
• Prior experience as a Data Scientist within a digital media is desirable
• Solid understanding of machine learning
• A degree in a quantitative field (e.g. economics, computer science, mathematics, statistics, engineering, physics, etc.)
• Experience with SQL/ Big Query/GMP tech stack / Clean rooms such as ADH
• A knack for statistical analysis and predictive modelling
• Good knowledge of R, Python
• Experience with SQL, MYSQL, PostgreSQL databases
• Knowledge of data management and visualization techniques
• Hands-on experience on BI/Visual Analytics Tools like PowerBI or Tableau or Data Studio
• Evidence of technical comfort and good understanding of internet functionality desirable
• Analytical pedigree - evidence of having approached problems from a mathematical perspective and working through to a solution in a logical way
• Proactive and results-oriented
• A positive, can-do attitude with a thirst to continually learn new things
• An ability to work independently and collaboratively with a wide range of teams
• Excellent communication skills, both written and oral

• Core Java: advanced level competency, should have worked on projects with core Java development.

• Linux shell : advanced level competency, work experience with Linux shell scripting, knowledge and experience to use important shell commands

• Rdbms, SQL: advanced level competency, Should have expertise in SQL query language syntax, should be well versed with aggregations, joins of SQL query language.

• Data structures and problem solving: should have ability to use appropriate data structure.

• AWS cloud : Good to have experience with aws serverless toolset along with aws infra

• Data Engineering ecosystem : Good to have experience and knowledge of data engineering, ETL, data warehouse (any toolset)

• Hadoop, HDFS, YARN : Should have introduction to internal working of these toolsets

• HIVE, MapReduce, Spark: Good to have experience developing transformations using hive queries, MapReduce job implementation and Spark Job Implementation. Spark implementation in Scala will be plus point.

• Airflow, Oozie, Sqoop, Zookeeper, Kafka: Good to have knowledge about purpose and working of these technology toolsets. Working experience will be a plus point here.

Location:  Pune/Nagpur,Goa,Hyderabad/Bangalore

Job Requirements:

• 9 years and above of total experience preferably in bigdata space.
• Creating spark applications using Scala to process data.
• Experience in scheduling and troubleshooting/debugging Spark jobs in steps.
• Experience in spark job performance tuning and optimizations.
• Should have experience in processing data using Kafka/Pyhton.
• Individual should have experience and understanding in configuring Kafka topics to optimize the performance.
• Should be proficient in writing SQL queries to process data in Data Warehouse.
• Hands on experience in working with Linux commands to troubleshoot/debug issues and creating shell scripts to automate tasks.
• Experience on AWS services like EMR.

Job Description:

We are looking for a Big Data Engineer who have worked across the entire ETL stack. Someone who has ingested data in a batch and live stream format, transformed large volumes of daily and built Data-warehouse to store the transformed data and has integrated different visualization dashboards and applications with the data stores.    The primary focus will be on choosing optimal solutions to use for these purposes, then maintaining, implementing, and monitoring them.

Responsibilities:

• Develop, test, and implement data solutions based on functional / non-functional business requirements.
• You would be required to code in Scala and PySpark daily on Cloud as well as on-prem infrastructure
• Build Data Models to store the data in a most optimized manner
• Identify, design, and implement process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Implementing the ETL process and optimal data pipeline architecture
• Monitoring performance and advising any necessary infrastructure changes.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.
• Proactively identify potential production issues and recommend and implement solutions
• Must be able to write quality code and build secure, highly available systems.
• Create design documents that describe the functionality, capacity, architecture, and process.
• Review peer-codes and pipelines before deploying to Production for optimization issues and code standards

Skill Sets:

• Good understanding of optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and ‘big data’ technologies.
• Proficient understanding of distributed computing principles
• Experience in working with batch processing/ real-time systems using various open-source technologies like NoSQL, Spark, Pig, Hive, Apache Airflow.
• Implemented complex projects dealing with the considerable data size (PB).
• Optimization techniques (performance, scalability, monitoring, etc.)
• Experience with integration of data from multiple data sources
• Experience with NoSQL databases, such as HBase, Cassandra, MongoDB, etc.,
• Knowledge of various ETL techniques and frameworks, such as Flume
• Experience with various messaging systems, such as Kafka or RabbitMQ
• Creation of DAGs for data engineering
• Expert at Python /Scala programming, especially for data engineering/ ETL purposes