{"id":800856,"url":"https://alion.io/job/particle41-data-science-engineering-lead","title":"Data Science & Engineering Lead","company":{"id":686023,"name":"Particle41","domain":"particle41.com","url":"https://alion.io/company/particle41-2","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"D","score":45,"open_postings":24,"ghost_share":0.917,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-30T05:48:23Z"}},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India","India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":28000,"max_usd":61000,"period":"year","method":"role_seniority_country_cell","sample_n":21},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Amazon Kinesis","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"Apache Iceberg","optional":false},{"name":"Apache Kafka","optional":false},{"name":"API Gateway","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Azure","optional":false},{"name":"Chain-of-Thought","optional":false},{"name":"CloudFormation","optional":false},{"name":"CNN","optional":false},{"name":"Computer Vision","optional":false},{"name":"CUDA","optional":false},{"name":"Databricks","optional":false},{"name":"DynamoDB","optional":false},{"name":"ElasticSearch","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GAN","optional":false},{"name":"Great Expectations","optional":false},{"name":"Hugging Face","optional":false},{"name":"IAM","optional":false},{"name":"LangChain","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"MySQL","optional":false},{"name":"NLP","optional":false},{"name":"NLTK","optional":false},{"name":"NumPy","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenCV","optional":false},{"name":"Pandas","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Power BI","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"TensorFlow","optional":false},{"name":"Terraform","optional":false},{"name":"Time Series","optional":false},{"name":"Transformers","optional":false}],"status":"live","first_seen_at":"2024-10-26T00:32:17Z","employer_posted_date":"2025-03-07","last_verified_at":"2026-10-30T22:00:58Z","board_verified":true,"closed_at":null,"days_open":734,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":733},"description":"Data Science & Engineering Lead\nLead the charge in AI and data innovation as our Data Science & Engineering Lead. Here, you’ll work hands-on with our talented team to build and deploy high-impact ML models, optimize our data systems, and drive actionable insights. If you’re skilled in advanced AI tools like Databricks, Spark, and Azure, and excited to push boundaries in machine learning and engineering, we want you on our team. Join us for meaningful work, a collaborative culture, and competitive benefits.\nIn This Role, You Will:\nDesign and implement supervised and unsupervised ML models (e.g., OLS, Logistic Regression, Ensemble Methods) to solve real-world business problems.\nLead model development for advanced architectures in neural networks, such as ANN, CNN, RNN, GAN, Transformers, and RESNet.\nDrive NLP advancements with tools like NLTK and neural-based language models.\nOversee the development of computer vision models, utilizing OpenCV for real-world applications.\nLead time-series modeling projects for forecasting and anomaly detection.\nUtilize AI techniques like Retrieval-Augmented Generation (RAG), Chain of Thought (CoT), and Model of Alignment (MOA) to enhance model performance.\nBuild and maintain scalable data pipelines for both streaming and batch processing.\nArchitect and optimize lakehouse solutions using Delta/Iceberg and bronze-silver-gold architectures.\nLead the development of ETL processes with tools like Airflow, DBT, and Airbyte to support data flow and transformation.\nDesign and optimize database models for OLTP and OLAP systems using Snowflake, SQL Server, PostgreSQL, and MySQL.\nDevelop NoSQL solutions, leveraging MongoDB, DynamoDB, and ElasticSearch for unstructured data.\nLead efforts in building cloud infrastructure, particularly in AWS (preferred) or Azure, using services such as Lambda, API Gateway, Batch processing, Kinesis, and Kafka.\nOversee MLOps pipelines for robust deployment of ML models in production with platforms like Sagemaker, Databricks, and Azure ML Studio.\nDevelop and optimize business intelligence dashboards with tools like Tableau, QuickSight, and PowerBI for actionable insights.\nImplement GPU acceleration and CUDA for model training and optimization.\nMentor junior team members in cutting-edge AI/ML techniques and best practices.\nSkills and Experience We Value:\nProven expertise in both supervised and unsupervised ML, advanced deep learning, including TensorFlow, PyTorch, and neural network architectures (e.g., CNN, GAN, Transformers).\nHands-on experience with machine learning libraries and tools such as Scikit-learn, Pandas, and Numpy.\nProficiency in AI model development using LLM libraries (e.g., Langchain, Huggingface, OpenAI).\nStrong MLOps skills, with experience deploying scalable pipelines in production using tools like Sagemaker, Databricks, and Azure ML Studio.\nAdvanced skills in big data frameworks like Apache Spark, Glue, and EMR for distributed model training.\nExpertise in ETL processes and data pipeline development with tools like Airflow, DBT, and Airbyte.\nStrong knowledge in lakehouse architectures (Delta/Iceberg) and experience with data quality frameworks like Great Expectations.\nProficiency in cloud platforms (AWS preferred or Azure), with a deep understanding of services like IAM, VPC networking, Lambda, API Gateway, Batch, Kinesis, and Kafka.\nProficiency with Infrastructure as Code (IaC) tools such as Terraform or CloudFormation for automation.\nAdvanced skills in GPU acceleration, CUDA, and distributed model training.\nDemonstrated ability to architect and deploy scalable machine learning and data-intensive systems.\nProficiency in database modeling for OLTP/OLAP systems and expertise with relational and NoSQL databases.\nStrong mentoring skills, with a proven track record of guiding junior team members in AI/ML best practices.\nBachelor’s degree in a related field (required), with a Master’s or PhD in Data Science or a related field (preferred).\n7+ years of experience in data science, machine learning, or data engineering.\nAWS or Azure certification (strongly preferred).\nStrong communication and leadership skills with experience working cross-functionally to deliver high-impact data solutions.\nAbout Particle41\n Our core values of Empowering, Leadership, Innovation, Teamwork, and Excellence drive everything we do to achieve the ultimate outcomes for our clients. Empowering Leadership for Innovation in Teamwork with Excellence ( ELITE )\nE - Empowering: Enabling individuals to reach their full potential.\nL - Leadership: Taking initiative and guiding each other toward success.\nI - Innovation: Embracing creativity and new ideas to stay ahead.\nT - Teamwork: Collaborating with empathy to achieve common goals.\n E - Excellence: Striving for the highest quality in everything we do.\nWe seek team members who embody these values and are committed to contributing to our mission. Particle41 welcomes individuals from all backgrounds who are committed to our mission and values. We provide equal employment opportunities to all employees and applicants, ensuring that hiring and employment decisions are based on merit and qualifications without discrimination based on race, color, religion, caste, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, local, or international laws. This policy applies to all aspects of employment and hiring. \nWe appreciate your interest and encourage applicants from these regions to apply. 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