- Adept at Machine learning techniques and algorithms.
Feature selection, dimensionality reduction, building and
- optimizing classifiers using machine learning techniques
- Data mining using state-of-the-art methods
- Doing ad-hoc analysis and presenting results
- Proficiency in using query languages such as N1QL, SQL
Experience with data visualization tools, such as D3.js, GGplot,
- Plotly, PyPlot, etc.
Creating automated anomaly detection systems and constant tracking
- of its performance
- Strong in Python is a must.
- Strong in Data Analysis and mining is a must
- Deep Learning, Neural Network, CNN, Image Processing (Must)
Building analytic systems - data collection, cleansing and
- integration
Experience with NoSQL databases, such as Couchbase, MongoDB,
Cassandra, HBase
About Accolite Software
Similar jobs
Who Are We?
Vahak (https://www.vahak.in) is India’s largest & most trusted online transport marketplace & directory for road transport businesses and individual commercial vehicle (Trucks, Trailers, Containers, Hyva, LCVs) owners for online truck and load booking, transport business branding and transport business network expansion. Lorry owners can find intercity and intracity loads from all over India and connect with other businesses to find trusted transporters and best deals in the Indian logistics services market. With the Vahak app, users can book loads and lorries from a live transport marketplace with over 5 Lakh + Transporters and Lorry owners in over 10,000+ locations for daily transport requirements.
Vahak has raised a capital of $5 Million in a “Pre Series A” round from RTP Global along with participation from Luxor Capital and Leo Capital. The other marquee angel investors include Kunal Shah, Founder and CEO, CRED; Jitendra Gupta, Founder and CEO, Jupiter; Vidit Aatrey and Sanjeev Barnwal, Co-founders, Meesho; Mohd Farid, Co-founder, Sharechat; Amrish Rau, CEO, Pine Labs; Harsimarbir Singh, Co-founder, Pristyn Care; Rohit and Kunal Bahl, Co-founders, Snapdeal; and Ravish Naresh, Co-founder and CEO, Khatabook.
Responsibilities for Data Analyst:
- Undertake preprocessing of structured and unstructured data
- Propose solutions and strategies to business challenges
- Present information using data visualization techniques
- Identify valuable data sources and automate collection processes
- Analyze large amounts of information to discover trends and patterns
- Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
- Proactively analyze data to answer key questions from stakeholders or out of self-initiated curiosity with an eye for what drives business performance.
Qualifications for Data Analyst
- Experience using business intelligence tools (e.g. Tableau, Power BI – not mandatory)
- Strong SQL or Excel skills with the ability to learn other analytic tools
- Conceptual understanding of various modelling techniques, pros and cons of each technique
- Strong problem solving skills with an emphasis on product development.
- Programming advanced computing, Developing algorithms and predictive modeling experience
- Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
- Advantage - Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
- Demonstrated experience applying data analysis methods to real-world data problems
We are looking for an exceptionally talented Lead data engineer who has exposure in implementing AWS services to build data pipelines, api integration and designing data warehouse. Candidate with both hands-on and leadership capabilities will be ideal for this position.
Qualification: At least a bachelor’s degree in Science, Engineering, Applied Mathematics. Preferred Masters degree
Job Responsibilities:
• Total 6+ years of experience as a Data Engineer and 2+ years of experience in managing a team
• Have minimum 3 years of AWS Cloud experience.
• Well versed in languages such as Python, PySpark, SQL, NodeJS etc
• Has extensive experience in Spark ecosystem and has worked on both real time and batch processing
• Have experience in AWS Glue, EMR, DMS, Lambda, S3, DynamoDB, Step functions, Airflow, RDS, Aurora etc.
• Experience with modern Database systems such as Redshift, Presto, Hive etc.
• Worked on building data lakes in the past on S3 or Apache Hudi
• Solid understanding of Data Warehousing Concepts
• Good to have experience on tools such as Kafka or Kinesis
• Good to have AWS Developer Associate or Solutions Architect Associate Certification
• Have experience in managing a team
- Minimum 1 years of relevant experience, in PySpark (mandatory)
- Hands on experience in development, test, deploy, maintain and improving data integration pipeline in AWS cloud environment is added plus
- Ability to play lead role and independently manage 3-5 member of Pyspark development team
- EMR ,Python and PYspark mandate.
- Knowledge and awareness working with AWS Cloud technologies like Apache Spark, , Glue, Kafka, Kinesis, and Lambda in S3, Redshift, RDS
- We are looking for a Data Engineer to build the next-generation mobile applications for our world-class fintech product.
- The candidate will be responsible for expanding and optimising our data and data pipeline architecture, as well as optimising data flow and collection for cross-functional teams.
- The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimising data systems and building them from the ground up.
- Looking for a person with a strong ability to analyse and provide valuable insights to the product and business team to solve daily business problems.
- You should be able to work in a high-volume environment, have outstanding planning and organisational skills.
Qualifications for Data Engineer
- Working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience building and optimising ‘big data’ data pipelines, architectures, and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with unstructured datasets. Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Looking for a candidate with 2-3 years of experience in a Data Engineer role, who is a CS graduate or has an equivalent experience.
What we're looking for?
- Experience with big data tools: Hadoop, Spark, Kafka and other alternate tools.
- Experience with relational SQL and NoSQL databases, including MySql/Postgres and Mongodb.
- Experience with data pipeline and workflow management tools: Luigi, Airflow.
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift.
- Experience with stream-processing systems: Storm, Spark-Streaming.
- Experience with object-oriented/object function scripting languages: Python, Java, Scala.
Work shift: Day time
- Strong problem-solving skills with an emphasis on product development.
insights from large data sets.
• Experience in building ML pipelines with Apache Spark, Python
• Proficiency in implementing end to end Data Science Life cycle
• Experience in Model fine-tuning and advanced grid search techniques
• Experience working with and creating data architectures.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural
networks, etc.) and their real-world advantages/drawbacks.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions,
statistical tests and proper usage, etc.) and experience with applications.
• Excellent written and verbal communication skills for coordinating across teams.
• A drive to learn and master new technologies and techniques.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Develop custom data models and algorithms to apply to data sets.
• Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting, and other business outcomes.
• Develop company A/B testing framework and test model quality.
• Coordinate with different functional teams to implement models and monitor outcomes.
• Develop processes and tools to monitor and analyze model performance and data accuracy.
Key skills:
● Strong knowledge in Data Science pipelines with Python
● Object-oriented programming
● A/B testing framework and model fine-tuning
● Proficiency in using sci-kit, NumPy, and pandas package in python
Nice to have:
● Ability to work with containerized solutions: Docker/Compose/Swarm/Kubernetes
● Unit testing, Test-driven development practice
● DevOps, Continuous integration/ continuous deployment experience
● Agile development environment experience, familiarity with SCRUM
● Deep learning knowledge
ETL specialist (for a startup hedge fund)
- We are looking for an experienced data engineer to join our team.
- The preprocessing involves ETL tasks, using pyspark, AWS Glue, staging data in parquet formats on S3, and Athena
To succeed in this data engineering position, you should care about well-documented, testable code and data integrity. We have devops who can help with AWS permissions.
We would like to build up a consistent data lake with staged, ready-to-use data, and to build up various scripts that will serve as blueprints for various additional data ingestion and transforms.
If you enjoy setting up something which many others will rely on, and have the relevant ETL expertise, we’d like to work with you.
Responsibilities
- Analyze and organize raw data
- Build data pipelines
- Prepare data for predictive modeling
- Explore ways to enhance data quality and reliability
- Potentially, collaborate with data scientists to support various experiments
Requirements
- Previous experience as a data engineer with the above technologies
● Ability to do exploratory analysis: Fetch data from systems and analyze trends.
● Developing customer segmentation models to improve the efficiency of marketing and product
campaigns.
● Establishing mechanisms for cross functional teams to consume customer insights to improve
engagement along the customer life cycle.
● Gather requirements for dashboards from business, marketing and operations stakeholders.
● Preparing internal reports for executive leadership and supporting their decision making.
● Analyse data, derive insights and embed it into Business actions.
● Work with cross functional teams.
Skills Required
• Data Analytics Visionary.
• Strong in SQL & Excel and good to have experience in Tableau.
• Experience in the field of Data Analysis, Data Visualization.
• Strong in analysing the Data and creating dashboards.
• Strong in communication, presentation and business intelligence.
• Multi-Dimensional, "Growth Hacker" Skill Set with strong sense of ownership for work.
• Aggressive “Take no prisoners” approach.
NLP Engineer - Artificial Intelligence
at Artivatic.ai